pipeline_tag stringclasses 48
values | library_name stringclasses 198
values | text stringlengths 1 900k | metadata stringlengths 2 438k | id stringlengths 5 122 | last_modified null | tags listlengths 1 1.84k | sha null | created_at stringlengths 25 25 | arxiv listlengths 0 201 | languages listlengths 0 1.83k | tags_str stringlengths 17 9.34k | text_str stringlengths 0 389k | text_lists listlengths 0 722 | processed_texts listlengths 1 723 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **BeamRiderNoFrameskip-v4**
This is a trained model of a **PPO** agent playing **BeamRiderNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for St... | {"library_name": "stable-baselines3", "tags": ["BeamRiderNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BeamRiderNoFrameskip-v4... | sb3/ppo-BeamRiderNoFrameskip-v4 | null | [
"stable-baselines3",
"BeamRiderNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T11:58:20+00:00 | [] | [] | TAGS
#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing BeamRiderNoFrameskip-v4
This is a trained model of a PPO agent playing BeamRiderNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents include... | [
"# PPO Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a PPO agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained age... | [
"TAGS\n#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a PPO agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | null |
# **Q-Learning** Agent playing **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="Jozaita/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attr... | {"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": ... | Jozaita/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-02T11:58:46+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
## Usage
| [
"# Q-Learning Agent playing FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n \n ## Usage"
] | [
"TAGS\n#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n",
"# Q-Learning Agent playing FrozenLake-v1\n This is a trained model of a Q-Learning agent playing FrozenLake-v1 .\n \n ## Usage"
] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **Ant-v3**
This is a trained model of a **PPO** agent playing **Ant-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcement lear... | {"library_name": "stable-baselines3", "tags": ["Ant-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Ant-v3", "type": "Ant-v3"}, "metrics": [... | sb3/ppo-Ant-v3 | null | [
"stable-baselines3",
"Ant-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T11:59:58+00:00 | [] | [] | TAGS
#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing Ant-v3
This is a trained model of a PPO agent playing Ant-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL... | [
"# PPO Agent playing Ant-v3\nThis is a trained model of a PPO agent playing Ant-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage (with ... | [
"TAGS\n#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing Ant-v3\nThis is a trained model of a PPO agent playing Ant-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\n... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Humanoid-v3**
This is a trained model of a **TD3** agent playing **Humanoid-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforc... | {"library_name": "stable-baselines3", "tags": ["Humanoid-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Humanoid-v3", "type": "Humanoid-v3"... | sb3/td3-Humanoid-v3 | null | [
"stable-baselines3",
"Humanoid-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:00:48+00:00 | [] | [] | TAGS
#stable-baselines3 #Humanoid-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Humanoid-v3
This is a trained model of a TD3 agent playing Humanoid-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 R... | [
"# TD3 Agent playing Humanoid-v3\nThis is a trained model of a TD3 agent playing Humanoid-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Us... | [
"TAGS\n#stable-baselines3 #Humanoid-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Humanoid-v3\nThis is a trained model of a TD3 agent playing Humanoid-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1197255800114339842/9pty... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/claregrall/1654175841134/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/claregrall | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T12:01:10+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Clare Grall
@claregrall
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
---------... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Walker2d-v3**
This is a trained model of a **TD3** agent playing **Walker2d-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforc... | {"library_name": "stable-baselines3", "tags": ["Walker2d-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2d-v3", "type": "Walker2d-v3"... | sb3/td3-Walker2d-v3 | null | [
"stable-baselines3",
"Walker2d-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:02:03+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2d-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Walker2d-v3
This is a trained model of a TD3 agent playing Walker2d-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 R... | [
"# TD3 Agent playing Walker2d-v3\nThis is a trained model of a TD3 agent playing Walker2d-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Us... | [
"TAGS\n#stable-baselines3 #Walker2d-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Walker2d-v3\nThis is a trained model of a TD3 agent playing Walker2d-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **HalfCheetah-v3**
This is a trained model of a **TD3** agent playing **HalfCheetah-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
re... | {"library_name": "stable-baselines3", "tags": ["HalfCheetah-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetah-v3", "type": "HalfCh... | sb3/td3-HalfCheetah-v3 | null | [
"stable-baselines3",
"HalfCheetah-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:02:50+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing HalfCheetah-v3
This is a trained model of a TD3 agent playing HalfCheetah-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with... | [
"# TD3 Agent playing HalfCheetah-v3\nThis is a trained model of a TD3 agent playing HalfCheetah-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing HalfCheetah-v3\nThis is a trained model of a TD3 agent playing HalfCheetah-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **AntBulletEnv-v0**
This is a trained model of a **TD3** agent playing **AntBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
... | {"library_name": "stable-baselines3", "tags": ["AntBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "AntB... | sb3/td3-AntBulletEnv-v0 | null | [
"stable-baselines3",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:03:37+00:00 | [] | [] | TAGS
#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing AntBulletEnv-v0
This is a trained model of a TD3 agent playing AntBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (wi... | [
"# TD3 Agent playing AntBulletEnv-v0\nThis is a trained model of a TD3 agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing AntBulletEnv-v0\nThis is a trained model of a TD3 agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framew... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Swimmer-v3**
This is a trained model of a **TD3** agent playing **Swimmer-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcem... | {"library_name": "stable-baselines3", "tags": ["Swimmer-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Swimmer-v3", "type": "Swimmer-v3"}, ... | sb3/td3-Swimmer-v3 | null | [
"stable-baselines3",
"Swimmer-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:04:40+00:00 | [] | [] | TAGS
#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Swimmer-v3
This is a trained model of a TD3 agent playing Swimmer-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL ... | [
"# TD3 Agent playing Swimmer-v3\nThis is a trained model of a TD3 agent playing Swimmer-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usag... | [
"TAGS\n#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Swimmer-v3\nThis is a trained model of a TD3 agent playing Swimmer-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Hopper-v3**
This is a trained model of a **TD3** agent playing **Hopper-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcemen... | {"library_name": "stable-baselines3", "tags": ["Hopper-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Hopper-v3", "type": "Hopper-v3"}, "me... | sb3/td3-Hopper-v3 | null | [
"stable-baselines3",
"Hopper-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:05:34+00:00 | [] | [] | TAGS
#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Hopper-v3
This is a trained model of a TD3 agent playing Hopper-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zo... | [
"# TD3 Agent playing Hopper-v3\nThis is a trained model of a TD3 agent playing Hopper-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage ... | [
"TAGS\n#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Hopper-v3\nThis is a trained model of a TD3 agent playing Hopper-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Bas... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1078115982768525317/wk6N... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/willsavino/1654175184979/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/willsavino | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T12:06:04+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Will Savino
@willsavino
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
---------... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **ReacherBulletEnv-v0**
This is a trained model of a **TD3** agent playing **ReacherBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Bas... | {"library_name": "stable-baselines3", "tags": ["ReacherBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ReacherBulletEnv-v0", "type... | sb3/td3-ReacherBulletEnv-v0 | null | [
"stable-baselines3",
"ReacherBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:06:32+00:00 | [] | [] | TAGS
#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing ReacherBulletEnv-v0
This is a trained model of a TD3 agent playing ReacherBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## U... | [
"# TD3 Agent playing ReacherBulletEnv-v0\nThis is a trained model of a TD3 agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents incl... | [
"TAGS\n#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing ReacherBulletEnv-v0\nThis is a trained model of a TD3 agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
text-generation | transformers |
# DistilGPT2-Beatles-Lyrics-finetuned-newlyrics
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the [Cmotions - Beatles lyrics](https://huggingface.co/datasets/cmotions/Beatles_lyrics) dataset. It will complete an input prompt with Beatles-like text.
## Model description
Mor... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": "cmotions/Beatles_lyrics", "widget": [{"text": "Last night in Kiev the", "example_title": "Kiev"}, {"text": "It hasn't rained in weeks", "example_title": "Rain"}], "model-index": [{"name": "DistilGPT2-Beatles-Lyrics-finetuned-newlyrics", "results... | wvangils/DistilGPT2-Beatles-Lyrics-finetuned-newlyrics | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"dataset:cmotions/Beatles_lyrics",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T12:07:10+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #dataset-cmotions/Beatles_lyrics #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| DistilGPT2-Beatles-Lyrics-finetuned-newlyrics
=============================================
This model is a fine-tuned version of distilgpt2 on the Cmotions - Beatles lyrics dataset. It will complete an input prompt with Beatles-like text.
Model description
-----------------
More information needed
Intended use... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #dataset-cmotions/Beatles_lyrics #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during tr... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **HopperBulletEnv-v0**
This is a trained model of a **TD3** agent playing **HopperBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Basel... | {"library_name": "stable-baselines3", "tags": ["HopperBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HopperBulletEnv-v0", "type":... | sb3/td3-HopperBulletEnv-v0 | null | [
"stable-baselines3",
"HopperBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:07:25+00:00 | [] | [] | TAGS
#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing HopperBulletEnv-v0
This is a trained model of a TD3 agent playing HopperBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usa... | [
"# TD3 Agent playing HopperBulletEnv-v0\nThis is a trained model of a TD3 agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents includ... | [
"TAGS\n#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing HopperBulletEnv-v0\nThis is a trained model of a TD3 agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **HalfCheetahBulletEnv-v0**
This is a trained model of a **TD3** agent playing **HalfCheetahBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for St... | {"library_name": "stable-baselines3", "tags": ["HalfCheetahBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetahBulletEnv-v0... | sb3/td3-HalfCheetahBulletEnv-v0 | null | [
"stable-baselines3",
"HalfCheetahBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:08:24+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing HalfCheetahBulletEnv-v0
This is a trained model of a TD3 agent playing HalfCheetahBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents include... | [
"# TD3 Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a TD3 agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained age... | [
"TAGS\n#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a TD3 agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Pendulum-v1**
This is a trained model of a **TD3** agent playing **Pendulum-v1**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforc... | {"library_name": "stable-baselines3", "tags": ["Pendulum-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pendulum-v1", "type": "Pendulum-v1"... | sb3/td3-Pendulum-v1 | null | [
"stable-baselines3",
"Pendulum-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:09:26+00:00 | [] | [] | TAGS
#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Pendulum-v1
This is a trained model of a TD3 agent playing Pendulum-v1
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 R... | [
"# TD3 Agent playing Pendulum-v1\nThis is a trained model of a TD3 agent playing Pendulum-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Us... | [
"TAGS\n#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Pendulum-v1\nThis is a trained model of a TD3 agent playing Pendulum-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
reinforcement-learning | null |
# **Q-Learning** Agent playing **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="Jozaita/q-Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
... | {"tags": ["Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-Taxi-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Taxi-v3", "type": "Taxi-v3"}, "metrics": [{"type": "mean_reward", "value": "7.54 +/... | Jozaita/q-Taxi-v3 | null | [
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-02T12:12:11+00:00 | [] | [] | TAGS
#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us
|
# Q-Learning Agent playing Taxi-v3
This is a trained model of a Q-Learning agent playing Taxi-v3 .
## Usage
| [
"# Q-Learning Agent playing Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n \n ## Usage"
] | [
"TAGS\n#Taxi-v3 #q-learning #reinforcement-learning #custom-implementation #model-index #region-us \n",
"# Q-Learning Agent playing Taxi-v3\n This is a trained model of a Q-Learning agent playing Taxi-v3 .\n \n ## Usage"
] |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1011998779061559297/5gOe... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/caballerogaudes/1654176335515/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/caballerogaudes | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T12:23:37+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
CesarCaballeroGaudes
@caballerogaudes
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training ... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **LunarLanderContinuous-v2**
This is a trained model of a **TD3** agent playing **LunarLanderContinuous-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["LunarLanderContinuous-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLanderContinuous-... | sb3/td3-LunarLanderContinuous-v2 | null | [
"stable-baselines3",
"LunarLanderContinuous-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:26:37+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing LunarLanderContinuous-v2
This is a trained model of a TD3 agent playing LunarLanderContinuous-v2
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# TD3 Agent playing LunarLanderContinuous-v2\nThis is a trained model of a TD3 agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing LunarLanderContinuous-v2\nThis is a trained model of a TD3 agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1532031893318737920/N4nw... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/quora-reddit/1654258179125/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/quora-reddit | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T12:30:18+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI CYBORG
Quora & Reddit
@quora-reddit
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
--... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-vios-v2
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2v... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["vivos_dataset"], "model-index": [{"name": "wav2vec2-base-vios-v2", "results": []}]} | tclong/wav2vec2-base-vios-v2 | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:vivos_dataset",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T12:30:49+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-vivos_dataset #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-vios-v2
=====================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the vivos\_dataset dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6056
* Wer: 0.2442
Model description
-----------------
More information needed
Intended uses & limita... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-vivos_dataset #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* t... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-hsb-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-hsb-colab", "results": []}]} | AAkhilesh/wav2vec2-large-xls-r-300m-hsb-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T12:43:01+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
|
# wav2vec2-large-xls-r-300m-hsb-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedu... | [
"# wav2vec2-large-xls-r-300m-hsb-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information neede... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"# wav2vec2-large-xls-r-300m-hsb-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voic... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **BipedalWalker-v3**
This is a trained model of a **TD3** agent playing **BipedalWalker-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines... | {"library_name": "stable-baselines3", "tags": ["BipedalWalker-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | sb3/td3-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T12:43:50+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing BipedalWalker-v3
This is a trained model of a TD3 agent playing BipedalWalker-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (... | [
"# TD3 Agent playing BipedalWalker-v3\nThis is a trained model of a TD3 agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included."... | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing BipedalWalker-v3\nThis is a trained model of a TD3 agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fra... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1279408626877304833/28Jt... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/vborghesani/1654178225151/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/vborghesani | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T12:54:30+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Valentina Borghesani
@vborghesani
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "c... | Ce/bert-finetuned-ner | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T12:57:41+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| bert-finetuned-ner
==================
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0649
* Precision: 0.9330
* Recall: 0.9485
* F1: 0.9407
* Accuracy: 0.9854
Model description
-----------------
More information ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **BipedalWalkerHardcore-v3**
This is a trained model of a **TD3** agent playing **BipedalWalkerHardcore-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["BipedalWalkerHardcore-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalkerHardcore-... | sb3/td3-BipedalWalkerHardcore-v3 | null | [
"stable-baselines3",
"BipedalWalkerHardcore-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:01:07+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalkerHardcore-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing BipedalWalkerHardcore-v3
This is a trained model of a TD3 agent playing BipedalWalkerHardcore-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# TD3 Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a TD3 agent playing BipedalWalkerHardcore-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #BipedalWalkerHardcore-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a TD3 agent playing BipedalWalkerHardcore-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1510853995690033153/-mRC... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/ppinheirochagas/1654190652962/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/ppinheirochagas | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T13:03:28+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Pedro Pinheiro-Chagas
@ppinheirochagas
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-ta-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-ta-colab", "results": []}]} | AAkhilesh/wav2vec2-large-xls-r-300m-ta-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T13:12:16+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
|
# wav2vec2-large-xls-r-300m-ta-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedur... | [
"# wav2vec2-large-xls-r-300m-ta-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"# wav2vec2-large-xls-r-300m-ta-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Walker2DBulletEnv-v0**
This is a trained model of a **TD3** agent playing **Walker2DBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable B... | {"library_name": "stable-baselines3", "tags": ["Walker2DBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2DBulletEnv-v0", "ty... | sb3/td3-Walker2DBulletEnv-v0 | null | [
"stable-baselines3",
"Walker2DBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:18:34+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Walker2DBulletEnv-v0
This is a trained model of a TD3 agent playing Walker2DBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
##... | [
"# TD3 Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a TD3 agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents in... | [
"TAGS\n#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a TD3 agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **MountainCarContinuous-v0**
This is a trained model of a **TD3** agent playing **MountainCarContinuous-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["MountainCarContinuous-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCarContinuous-... | sb3/td3-MountainCarContinuous-v0 | null | [
"stable-baselines3",
"MountainCarContinuous-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:19:42+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing MountainCarContinuous-v0
This is a trained model of a TD3 agent playing MountainCarContinuous-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# TD3 Agent playing MountainCarContinuous-v0\nThis is a trained model of a TD3 agent playing MountainCarContinuous-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing MountainCarContinuous-v0\nThis is a trained model of a TD3 agent playing MountainCarContinuous-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
null | null | test | {} | osanseviero/test_tacotron | null | [
"region:us"
] | null | 2022-06-02T13:19:51+00:00 | [] | [] | TAGS
#region-us
| test | [] | [
"TAGS\n#region-us \n"
] |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-hsb-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-hsb-colab", "results": []}]} | brindap/wav2vec2-large-xls-r-300m-hsb-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T13:24:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hsb-colab
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:
* Loss: 3.2283
* Wer: 0.9818
Model description
-----------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* t... |
null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | lmazzon70/identify-my-cat | null | [
"fastai",
"region:us"
] | null | 2022-06-02T13:24:29+00:00 | [] | [] | TAGS
#fastai #region-us
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentation here).\n\n3. Join the fastai co... | [
"TAGS\n#fastai #region-us \n",
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentatio... |
null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | lmazzon70/blurr_IMDB_distilbert_classification | null | [
"fastai",
"region:us"
] | null | 2022-06-02T13:30:34+00:00 | [] | [] | TAGS
#fastai #region-us
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentation here).\n\n3. Join the fastai co... | [
"TAGS\n#fastai #region-us \n",
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentatio... |
reinforcement-learning | stable-baselines3 |
# **TD3** Agent playing **Ant-v3**
This is a trained model of a **TD3** agent playing **Ant-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcement lear... | {"library_name": "stable-baselines3", "tags": ["Ant-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TD3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Ant-v3", "type": "Ant-v3"}, "metrics": [... | sb3/td3-Ant-v3 | null | [
"stable-baselines3",
"Ant-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:33:20+00:00 | [] | [] | TAGS
#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TD3 Agent playing Ant-v3
This is a trained model of a TD3 agent playing Ant-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL... | [
"# TD3 Agent playing Ant-v3\nThis is a trained model of a TD3 agent playing Ant-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage (with ... | [
"TAGS\n#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TD3 Agent playing Ant-v3\nThis is a trained model of a TD3 agent playing Ant-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\n... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **PongNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **PongNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable B... | {"library_name": "stable-baselines3", "tags": ["PongNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PongNoFrameskip-v4", "type... | sb3/qrdqn-PongNoFrameskip-v4 | null | [
"stable-baselines3",
"PongNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:34:15+00:00 | [] | [] | TAGS
#stable-baselines3 #PongNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing PongNoFrameskip-v4
This is a trained model of a QRDQN agent playing PongNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
##... | [
"# QRDQN Agent playing PongNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing PongNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents in... | [
"TAGS\n#stable-baselines3 #PongNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing PongNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing PongNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tr... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **LunarLander-v2**
This is a trained model of a **QRDQN** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "Luna... | sb3/qrdqn-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:35:33+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing LunarLander-v2
This is a trained model of a QRDQN agent playing LunarLander-v2
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (... | [
"# QRDQN Agent playing LunarLander-v2\nThis is a trained model of a QRDQN agent playing LunarLander-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included."... | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing LunarLander-v2\nThis is a trained model of a QRDQN agent playing LunarLander-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training frame... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **MountainCar-v0**
This is a trained model of a **QRDQN** agent playing **MountainCar-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines... | {"library_name": "stable-baselines3", "tags": ["MountainCar-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCar-v0", "type": "Moun... | sb3/qrdqn-MountainCar-v0 | null | [
"stable-baselines3",
"MountainCar-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:36:23+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCar-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing MountainCar-v0
This is a trained model of a QRDQN agent playing MountainCar-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (... | [
"# QRDQN Agent playing MountainCar-v0\nThis is a trained model of a QRDQN agent playing MountainCar-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included."... | [
"TAGS\n#stable-baselines3 #MountainCar-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing MountainCar-v0\nThis is a trained model of a QRDQN agent playing MountainCar-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training frame... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **Acrobot-v1**
This is a trained model of a **QRDQN** agent playing **Acrobot-v1**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinfo... | {"library_name": "stable-baselines3", "tags": ["Acrobot-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Acrobot-v1", "type": "Acrobot-v1"}... | sb3/qrdqn-Acrobot-v1 | null | [
"stable-baselines3",
"Acrobot-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:37:14+00:00 | [] | [] | TAGS
#stable-baselines3 #Acrobot-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing Acrobot-v1
This is a trained model of a QRDQN agent playing Acrobot-v1
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3... | [
"# QRDQN Agent playing Acrobot-v1\nThis is a trained model of a QRDQN agent playing Acrobot-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## ... | [
"TAGS\n#stable-baselines3 #Acrobot-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing Acrobot-v1\nThis is a trained model of a QRDQN agent playing Acrobot-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Sta... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **EnduroNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **EnduroNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stab... | {"library_name": "stable-baselines3", "tags": ["EnduroNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "EnduroNoFrameskip-v4", "... | sb3/qrdqn-EnduroNoFrameskip-v4 | null | [
"stable-baselines3",
"EnduroNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:38:00+00:00 | [] | [] | TAGS
#stable-baselines3 #EnduroNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing EnduroNoFrameskip-v4
This is a trained model of a QRDQN agent playing EnduroNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.... | [
"# QRDQN Agent playing EnduroNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing EnduroNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agent... | [
"TAGS\n#stable-baselines3 #EnduroNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing EnduroNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing EnduroNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo i... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **RoadRunnerNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **RoadRunnerNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework ... | {"library_name": "stable-baselines3", "tags": ["RoadRunnerNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "RoadRunnerNoFrameski... | sb3/qrdqn-RoadRunnerNoFrameskip-v4 | null | [
"stable-baselines3",
"RoadRunnerNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:46:21+00:00 | [] | [] | TAGS
#stable-baselines3 #RoadRunnerNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing RoadRunnerNoFrameskip-v4
This is a trained model of a QRDQN agent playing RoadRunnerNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents i... | [
"# QRDQN Agent playing RoadRunnerNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing RoadRunnerNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-train... | [
"TAGS\n#stable-baselines3 #RoadRunnerNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing RoadRunnerNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing RoadRunnerNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\n... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training fram... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFr... | sb3/qrdqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:47:35+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a QRDQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained ag... | [
"# QRDQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre... | [
"TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **BreakoutNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **BreakoutNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["BreakoutNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BreakoutNoFrameskip-v4... | sb3/qrdqn-BreakoutNoFrameskip-v4 | null | [
"stable-baselines3",
"BreakoutNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:49:03+00:00 | [] | [] | TAGS
#stable-baselines3 #BreakoutNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing BreakoutNoFrameskip-v4
This is a trained model of a QRDQN agent playing BreakoutNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# QRDQN Agent playing BreakoutNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing BreakoutNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #BreakoutNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing BreakoutNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing BreakoutNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **SeaquestNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **SeaquestNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["SeaquestNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SeaquestNoFrameskip-v4... | sb3/qrdqn-SeaquestNoFrameskip-v4 | null | [
"stable-baselines3",
"SeaquestNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:50:58+00:00 | [] | [] | TAGS
#stable-baselines3 #SeaquestNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing SeaquestNoFrameskip-v4
This is a trained model of a QRDQN agent playing SeaquestNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# QRDQN Agent playing SeaquestNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing SeaquestNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #SeaquestNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing SeaquestNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing SeaquestNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **AsteroidsNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **AsteroidsNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework fo... | {"library_name": "stable-baselines3", "tags": ["AsteroidsNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AsteroidsNoFrameskip-... | sb3/qrdqn-AsteroidsNoFrameskip-v4 | null | [
"stable-baselines3",
"AsteroidsNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:52:40+00:00 | [] | [] | TAGS
#stable-baselines3 #AsteroidsNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing AsteroidsNoFrameskip-v4
This is a trained model of a QRDQN agent playing AsteroidsNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inc... | [
"# QRDQN Agent playing AsteroidsNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing AsteroidsNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained... | [
"TAGS\n#stable-baselines3 #AsteroidsNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing AsteroidsNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing AsteroidsNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **QbertNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **QbertNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable... | {"library_name": "stable-baselines3", "tags": ["QbertNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "QbertNoFrameskip-v4", "ty... | sb3/qrdqn-QbertNoFrameskip-v4 | null | [
"stable-baselines3",
"QbertNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:53:59+00:00 | [] | [] | TAGS
#stable-baselines3 #QbertNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing QbertNoFrameskip-v4
This is a trained model of a QRDQN agent playing QbertNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
... | [
"# QRDQN Agent playing QbertNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing QbertNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents ... | [
"TAGS\n#stable-baselines3 #QbertNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing QbertNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing QbertNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **BeamRiderNoFrameskip-v4**
This is a trained model of a **QRDQN** agent playing **BeamRiderNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework fo... | {"library_name": "stable-baselines3", "tags": ["BeamRiderNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BeamRiderNoFrameskip-... | sb3/qrdqn-BeamRiderNoFrameskip-v4 | null | [
"stable-baselines3",
"BeamRiderNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:55:17+00:00 | [] | [] | TAGS
#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing BeamRiderNoFrameskip-v4
This is a trained model of a QRDQN agent playing BeamRiderNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inc... | [
"# QRDQN Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained... | [
"TAGS\n#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a QRDQN agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe... |
reinforcement-learning | stable-baselines3 |
# **QRDQN** Agent playing **CartPole-v1**
This is a trained model of a **QRDQN** agent playing **CartPole-v1**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
rein... | {"library_name": "stable-baselines3", "tags": ["CartPole-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "QRDQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v... | sb3/qrdqn-CartPole-v1 | null | [
"stable-baselines3",
"CartPole-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T13:58:44+00:00 | [] | [] | TAGS
#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# QRDQN Agent playing CartPole-v1
This is a trained model of a QRDQN agent playing CartPole-v1
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with S... | [
"# QRDQN Agent playing CartPole-v1\nThis is a trained model of a QRDQN agent playing CartPole-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"#... | [
"TAGS\n#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# QRDQN Agent playing CartPole-v1\nThis is a trained model of a QRDQN agent playing CartPole-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for ... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **PongNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **PongNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Basel... | {"library_name": "stable-baselines3", "tags": ["PongNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PongNoFrameskip-v4", "type":... | sb3/a2c-PongNoFrameskip-v4 | null | [
"stable-baselines3",
"PongNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:14:59+00:00 | [] | [] | TAGS
#stable-baselines3 #PongNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing PongNoFrameskip-v4
This is a trained model of a A2C agent playing PongNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usa... | [
"# A2C Agent playing PongNoFrameskip-v4\nThis is a trained model of a A2C agent playing PongNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents includ... | [
"TAGS\n#stable-baselines3 #PongNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing PongNoFrameskip-v4\nThis is a trained model of a A2C agent playing PongNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **LunarLander-v2**
This is a trained model of a **A2C** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
re... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | sb3/a2c-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:16:30+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing LunarLander-v2
This is a trained model of a A2C agent playing LunarLander-v2
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with... | [
"# A2C Agent playing LunarLander-v2\nThis is a trained model of a A2C agent playing LunarLander-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing LunarLander-v2\nThis is a trained model of a A2C agent playing LunarLander-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **Acrobot-v1**
This is a trained model of a **A2C** agent playing **Acrobot-v1**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcem... | {"library_name": "stable-baselines3", "tags": ["Acrobot-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Acrobot-v1", "type": "Acrobot-v1"}, ... | sb3/a2c-Acrobot-v1 | null | [
"stable-baselines3",
"Acrobot-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:17:27+00:00 | [] | [] | TAGS
#stable-baselines3 #Acrobot-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing Acrobot-v1
This is a trained model of a A2C agent playing Acrobot-v1
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL ... | [
"# A2C Agent playing Acrobot-v1\nThis is a trained model of a A2C agent playing Acrobot-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usag... | [
"TAGS\n#stable-baselines3 #Acrobot-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing Acrobot-v1\nThis is a trained model of a A2C agent playing Acrobot-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
image-classification | transformers |
# apes
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
... | {"tags": ["image-classification", "pytorch", "huggingpics"], "metrics": ["accuracy"]} | ducnapa/apes | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:17:46+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# apes
Autogenerated by HuggingPics️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
## Example Images
#### chimpanzee
!chimpanzee
#### gibbon
!gibbon
#### gorilla
!gorilla
#### orangutan
!orangutan | [
"# apes\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.",
"## Example Images",
"#### chimpanzee\n\n!chimpanzee",
"#### gibbon\n\n!gibbon",
"#### gorilla\n\n!gorilla",
"#### orang... | [
"TAGS\n#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# apes\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **HalfCheetah-v3**
This is a trained model of a **A2C** agent playing **HalfCheetah-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
re... | {"library_name": "stable-baselines3", "tags": ["HalfCheetah-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetah-v3", "type": "HalfCh... | sb3/a2c-HalfCheetah-v3 | null | [
"stable-baselines3",
"HalfCheetah-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:18:12+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing HalfCheetah-v3
This is a trained model of a A2C agent playing HalfCheetah-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with... | [
"# A2C Agent playing HalfCheetah-v3\nThis is a trained model of a A2C agent playing HalfCheetah-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing HalfCheetah-v3\nThis is a trained model of a A2C agent playing HalfCheetah-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **AntBulletEnv-v0**
This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
... | {"library_name": "stable-baselines3", "tags": ["AntBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "AntB... | sb3/a2c-AntBulletEnv-v0 | null | [
"stable-baselines3",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"has_space",
"region:us"
] | null | 2022-06-02T14:19:00+00:00 | [] | [] | TAGS
#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #has_space #region-us
|
# A2C Agent playing AntBulletEnv-v0
This is a trained model of a A2C agent playing AntBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (wi... | [
"# A2C Agent playing AntBulletEnv-v0\nThis is a trained model of a A2C agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #has_space #region-us \n",
"# A2C Agent playing AntBulletEnv-v0\nThis is a trained model of a A2C agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a trai... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Base-960h
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/)
The base model pretrained and fine-tuned on 960 hours of Librispeech on 16kHz sampled speech audio. When using the model
make sure that your speech input is also sampled at 16Khz.
[Pa... | {"language": "en", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard"], "datasets": ["librispeech_asr"], "widget": [{"example_title": "Librispeech sample 1", "src": "https://cdn-media.huggingface.co/speech_samples/sample1.flac"}, {"example_title": "Librispeech sample 2", "sr... | Classroom-workshop/assignment1-omar | null | [
"transformers",
"pytorch",
"tf",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2006.11477",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:19:00+00:00 | [
"2006.11477"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2006.11477 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| Wav2Vec2-Base-960h
==================
Facebook's Wav2Vec2
The base model pretrained and fine-tuned on 960 hours of Librispeech on 16kHz sampled speech audio. When using the model
make sure that your speech input is also sampled at 16Khz.
Paper
Authors: Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, Michael Au... | [] | [
"TAGS\n#transformers #pytorch #tf #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2006.11477 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **Swimmer-v3**
This is a trained model of a **A2C** agent playing **Swimmer-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcem... | {"library_name": "stable-baselines3", "tags": ["Swimmer-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Swimmer-v3", "type": "Swimmer-v3"}, ... | sb3/a2c-Swimmer-v3 | null | [
"stable-baselines3",
"Swimmer-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:20:10+00:00 | [] | [] | TAGS
#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing Swimmer-v3
This is a trained model of a A2C agent playing Swimmer-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL ... | [
"# A2C Agent playing Swimmer-v3\nThis is a trained model of a A2C agent playing Swimmer-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usag... | [
"TAGS\n#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing Swimmer-v3\nThis is a trained model of a A2C agent playing Swimmer-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
automatic-speech-recognition | transformers |
# S2T-SMALL-LIBRISPEECH-ASR
`s2t-small-librispeech-asr` is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in [this paper](https://arxiv.org/abs/2010.05171) and released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/sp... | {"language": "en", "license": "mit", "tags": ["speech", "audio", "automatic-speech-recognition", "hf-asr-leaderboard"], "datasets": ["librispeech_asr"], "pipeline_tag": "automatic-speech-recognition", "widget": [{"example_title": "Librispeech sample 1", "src": "https://cdn-media.huggingface.co/speech_samples/sample1.fl... | Classroom-workshop/assignment1-jane | null | [
"transformers",
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"speech",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"arxiv:1904.08779",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:20:45+00:00 | [
"2010.05171",
"1904.08779"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us
| S2T-SMALL-LIBRISPEECH-ASR
=========================
's2t-small-librispeech-asr' is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in this paper and released in
this repository
Model description
-----------------
S2T is an end-to-end sequence-to-... | [
"### How to use\n\n\nAs this a standard sequence to sequence transformer model, you can use the 'generate' method to generate the\ntranscripts by passing the speech features to the model.\n\n\n*Note: The 'Speech2TextProcessor' object uses torchaudio to extract the\nfilter bank features. Make sure to install the 'to... | [
"TAGS\n#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us \n",
"### How to use\n\n\nAs this a standard sequence to sequence transform... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **EnduroNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **EnduroNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable B... | {"library_name": "stable-baselines3", "tags": ["EnduroNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "EnduroNoFrameskip-v4", "ty... | sb3/a2c-EnduroNoFrameskip-v4 | null | [
"stable-baselines3",
"EnduroNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:21:05+00:00 | [] | [] | TAGS
#stable-baselines3 #EnduroNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing EnduroNoFrameskip-v4
This is a trained model of a A2C agent playing EnduroNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
##... | [
"# A2C Agent playing EnduroNoFrameskip-v4\nThis is a trained model of a A2C agent playing EnduroNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents in... | [
"TAGS\n#stable-baselines3 #EnduroNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing EnduroNoFrameskip-v4\nThis is a trained model of a A2C agent playing EnduroNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
automatic-speech-recognition | transformers |
# S2T-SMALL-LIBRISPEECH-ASR
`s2t-small-librispeech-asr` is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in [this paper](https://arxiv.org/abs/2010.05171) and released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/sp... | {"language": "en", "license": "mit", "tags": ["speech", "audio", "automatic-speech-recognition", "hf-asr-leaderboard"], "datasets": ["librispeech_asr"], "pipeline_tag": "automatic-speech-recognition", "widget": [{"example_title": "Librispeech sample 1", "src": "https://cdn-media.huggingface.co/speech_samples/sample1.fl... | Classroom-workshop/assignment1-jack | null | [
"transformers",
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"speech",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"arxiv:1904.08779",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:22:08+00:00 | [
"2010.05171",
"1904.08779"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us
| S2T-SMALL-LIBRISPEECH-ASR
=========================
's2t-small-librispeech-asr' is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in this paper and released in
this repository
Model description
-----------------
S2T is an end-to-end sequence-to-... | [
"### How to use\n\n\nAs this a standard sequence to sequence transformer model, you can use the 'generate' method to generate the\ntranscripts by passing the speech features to the model.\n\n\n*Note: The 'Speech2TextProcessor' object uses torchaudio to extract the\nfilter bank features. Make sure to install the 'to... | [
"TAGS\n#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us \n",
"### How to use\n\n\nAs this a standard sequence to sequence transform... |
automatic-speech-recognition | transformers |
# S2T-SMALL-LIBRISPEECH-ASR
`s2t-small-librispeech-asr` is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in [this paper](https://arxiv.org/abs/2010.05171) and released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/sp... | {"language": "en", "license": "mit", "tags": ["speech", "audio", "automatic-speech-recognition", "hf-asr-leaderboard"], "datasets": ["librispeech_asr"], "pipeline_tag": "automatic-speech-recognition", "widget": [{"example_title": "Librispeech sample 1", "src": "https://cdn-media.huggingface.co/speech_samples/sample1.fl... | Classroom-workshop/assignment1-joane | null | [
"transformers",
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"speech",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"arxiv:1904.08779",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:22:43+00:00 | [
"2010.05171",
"1904.08779"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us
| S2T-SMALL-LIBRISPEECH-ASR
=========================
's2t-small-librispeech-asr' is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in this paper and released in
this repository
Model description
-----------------
S2T is an end-to-end sequence-to-... | [
"### How to use\n\n\nAs this a standard sequence to sequence transformer model, you can use the 'generate' method to generate the\ntranscripts by passing the speech features to the model.\n\n\n*Note: The 'Speech2TextProcessor' object uses torchaudio to extract the\nfilter bank features. Make sure to install the 'to... | [
"TAGS\n#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us \n",
"### How to use\n\n\nAs this a standard sequence to sequence transform... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **Hopper-v3**
This is a trained model of a **A2C** agent playing **Hopper-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcemen... | {"library_name": "stable-baselines3", "tags": ["Hopper-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Hopper-v3", "type": "Hopper-v3"}, "me... | sb3/a2c-Hopper-v3 | null | [
"stable-baselines3",
"Hopper-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:23:04+00:00 | [] | [] | TAGS
#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing Hopper-v3
This is a trained model of a A2C agent playing Hopper-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zo... | [
"# A2C Agent playing Hopper-v3\nThis is a trained model of a A2C agent playing Hopper-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage ... | [
"TAGS\n#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing Hopper-v3\nThis is a trained model of a A2C agent playing Hopper-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Bas... |
automatic-speech-recognition | transformers |
# S2T-SMALL-LIBRISPEECH-ASR
`s2t-small-librispeech-asr` is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in [this paper](https://arxiv.org/abs/2010.05171) and released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/sp... | {"language": "en", "license": "mit", "tags": ["speech", "audio", "automatic-speech-recognition", "hf-asr-leaderboard"], "datasets": ["librispeech_asr"], "pipeline_tag": "automatic-speech-recognition", "widget": [{"example_title": "Librispeech sample 1", "src": "https://cdn-media.huggingface.co/speech_samples/sample1.fl... | Classroom-workshop/assignment1-maria | null | [
"transformers",
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"speech",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"arxiv:1904.08779",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:23:58+00:00 | [
"2010.05171",
"1904.08779"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us
| S2T-SMALL-LIBRISPEECH-ASR
=========================
's2t-small-librispeech-asr' is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in this paper and released in
this repository
Model description
-----------------
S2T is an end-to-end sequence-to-... | [
"### How to use\n\n\nAs this a standard sequence to sequence transformer model, you can use the 'generate' method to generate the\ntranscripts by passing the speech features to the model.\n\n\n*Note: The 'Speech2TextProcessor' object uses torchaudio to extract the\nfilter bank features. Make sure to install the 'to... | [
"TAGS\n#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us \n",
"### How to use\n\n\nAs this a standard sequence to sequence transform... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **RoadRunnerNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **RoadRunnerNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["RoadRunnerNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "RoadRunnerNoFrameskip-... | sb3/a2c-RoadRunnerNoFrameskip-v4 | null | [
"stable-baselines3",
"RoadRunnerNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:24:00+00:00 | [] | [] | TAGS
#stable-baselines3 #RoadRunnerNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing RoadRunnerNoFrameskip-v4
This is a trained model of a A2C agent playing RoadRunnerNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# A2C Agent playing RoadRunnerNoFrameskip-v4\nThis is a trained model of a A2C agent playing RoadRunnerNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #RoadRunnerNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing RoadRunnerNoFrameskip-v4\nThis is a trained model of a A2C agent playing RoadRunnerNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
automatic-speech-recognition | transformers |
# S2T-SMALL-LIBRISPEECH-ASR
`s2t-small-librispeech-asr` is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in [this paper](https://arxiv.org/abs/2010.05171) and released in
[this repository](https://github.com/pytorch/fairseq/tree/master/examples/sp... | {"language": "en", "license": "mit", "tags": ["speech", "audio", "automatic-speech-recognition", "hf-asr-leaderboard"], "datasets": ["librispeech_asr"], "pipeline_tag": "automatic-speech-recognition", "widget": [{"example_title": "Librispeech sample 1", "src": "https://cdn-media.huggingface.co/speech_samples/sample1.fl... | Classroom-workshop/assignment1-francesco | null | [
"transformers",
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"speech",
"audio",
"hf-asr-leaderboard",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"arxiv:1904.08779",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:24:33+00:00 | [
"2010.05171",
"1904.08779"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us
| S2T-SMALL-LIBRISPEECH-ASR
=========================
's2t-small-librispeech-asr' is a Speech to Text Transformer (S2T) model trained for automatic speech recognition (ASR).
The S2T model was proposed in this paper and released in
this repository
Model description
-----------------
S2T is an end-to-end sequence-to-... | [
"### How to use\n\n\nAs this a standard sequence to sequence transformer model, you can use the 'generate' method to generate the\ntranscripts by passing the speech features to the model.\n\n\n*Note: The 'Speech2TextProcessor' object uses torchaudio to extract the\nfilter bank features. Make sure to install the 'to... | [
"TAGS\n#transformers #pytorch #tf #speech_to_text #automatic-speech-recognition #speech #audio #hf-asr-leaderboard #en #dataset-librispeech_asr #arxiv-2010.05171 #arxiv-1904.08779 #license-mit #model-index #endpoints_compatible #region-us \n",
"### How to use\n\n\nAs this a standard sequence to sequence transform... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **ReacherBulletEnv-v0**
This is a trained model of a **A2C** agent playing **ReacherBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Bas... | {"library_name": "stable-baselines3", "tags": ["ReacherBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ReacherBulletEnv-v0", "type... | sb3/a2c-ReacherBulletEnv-v0 | null | [
"stable-baselines3",
"ReacherBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:24:56+00:00 | [] | [] | TAGS
#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing ReacherBulletEnv-v0
This is a trained model of a A2C agent playing ReacherBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## U... | [
"# A2C Agent playing ReacherBulletEnv-v0\nThis is a trained model of a A2C agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents incl... | [
"TAGS\n#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing ReacherBulletEnv-v0\nThis is a trained model of a A2C agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | sb3/a2c-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"has_space",
"region:us"
] | null | 2022-06-02T14:25:50+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #has_space #region-us
|
# A2C Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a A2C agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
"# A2C Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a A2C agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-tra... | [
"TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #has_space #region-us \n",
"# A2C Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a A2C agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **HopperBulletEnv-v0**
This is a trained model of a **A2C** agent playing **HopperBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Basel... | {"library_name": "stable-baselines3", "tags": ["HopperBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HopperBulletEnv-v0", "type":... | sb3/a2c-HopperBulletEnv-v0 | null | [
"stable-baselines3",
"HopperBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:26:51+00:00 | [] | [] | TAGS
#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing HopperBulletEnv-v0
This is a trained model of a A2C agent playing HopperBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usa... | [
"# A2C Agent playing HopperBulletEnv-v0\nThis is a trained model of a A2C agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents includ... | [
"TAGS\n#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing HopperBulletEnv-v0\nThis is a trained model of a A2C agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Classroom-workshop/assignment2-francesco | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:27:00+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Classroom-workshop/assignment2-llama | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:27:20+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Classroom-workshop/assignment2-julien | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:27:27+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Classroom-workshop/assignment2-omar | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:27:33+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **HalfCheetahBulletEnv-v0**
This is a trained model of a **A2C** agent playing **HalfCheetahBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for St... | {"library_name": "stable-baselines3", "tags": ["HalfCheetahBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetahBulletEnv-v0... | sb3/a2c-HalfCheetahBulletEnv-v0 | null | [
"stable-baselines3",
"HalfCheetahBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:27:51+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing HalfCheetahBulletEnv-v0
This is a trained model of a A2C agent playing HalfCheetahBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents include... | [
"# A2C Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a A2C agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained age... | [
"TAGS\n#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a A2C agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Classroom-workshop/assignment2-thom | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:27:52+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Classroom-workshop/assignment2-llamas | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:28:07+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-sst-2-english-finetuned-sst2
This model is a fine-tuned version of [distilbert-base-uncased-fi... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy"], "model-index": [{"name": "distilbert-base-uncased-finetuned-sst-2-english-finetuned-sst2", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type":... | etch/distilbert-base-uncased-finetuned-sst-2-english-finetuned-sst2 | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:28:55+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-sst-2-english-finetuned-sst2
==============================================================
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the glue dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3950
* Accuracy:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **Pendulum-v1**
This is a trained model of a **A2C** agent playing **Pendulum-v1**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforc... | {"library_name": "stable-baselines3", "tags": ["Pendulum-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pendulum-v1", "type": "Pendulum-v1"... | sb3/a2c-Pendulum-v1 | null | [
"stable-baselines3",
"Pendulum-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:28:57+00:00 | [] | [] | TAGS
#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing Pendulum-v1
This is a trained model of a A2C agent playing Pendulum-v1
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 R... | [
"# A2C Agent playing Pendulum-v1\nThis is a trained model of a A2C agent playing Pendulum-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Us... | [
"TAGS\n#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing Pendulum-v1\nThis is a trained model of a A2C agent playing Pendulum-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
feature-extraction | transformers | # Jeux2BERT
Jeux2BERT is a Flaubert language model augmented by the lexico-semantic network JeuxDeMots.
Thus, this model tries to capture the distributional and relational properties of words, but also tries to discriminate the different relational properties between words or syntagms.
The Web application includes t... | {} | Massinissa/Jeux2BERT | null | [
"transformers",
"pytorch",
"flaubert",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:46:03+00:00 | [] | [] | TAGS
#transformers #pytorch #flaubert #feature-extraction #endpoints_compatible #region-us
| # Jeux2BERT
Jeux2BERT is a Flaubert language model augmented by the lexico-semantic network JeuxDeMots.
Thus, this model tries to capture the distributional and relational properties of words, but also tries to discriminate the different relational properties between words or syntagms.
The Web application includes t... | [
"# Jeux2BERT\n\nJeux2BERT is a Flaubert language model augmented by the lexico-semantic network JeuxDeMots. \nThus, this model tries to capture the distributional and relational properties of words, but also tries to discriminate the different relational properties between words or syntagms.\n\nThe Web application ... | [
"TAGS\n#transformers #pytorch #flaubert #feature-extraction #endpoints_compatible #region-us \n",
"# Jeux2BERT\n\nJeux2BERT is a Flaubert language model augmented by the lexico-semantic network JeuxDeMots. \nThus, this model tries to capture the distributional and relational properties of words, but also tries to... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **SeaquestNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **SeaquestNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stab... | {"library_name": "stable-baselines3", "tags": ["SeaquestNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SeaquestNoFrameskip-v4",... | sb3/a2c-SeaquestNoFrameskip-v4 | null | [
"stable-baselines3",
"SeaquestNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:46:06+00:00 | [] | [] | TAGS
#stable-baselines3 #SeaquestNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing SeaquestNoFrameskip-v4
This is a trained model of a A2C agent playing SeaquestNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.... | [
"# A2C Agent playing SeaquestNoFrameskip-v4\nThis is a trained model of a A2C agent playing SeaquestNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agent... | [
"TAGS\n#stable-baselines3 #SeaquestNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing SeaquestNoFrameskip-v4\nThis is a trained model of a A2C agent playing SeaquestNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **AsteroidsNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **AsteroidsNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for St... | {"library_name": "stable-baselines3", "tags": ["AsteroidsNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AsteroidsNoFrameskip-v4... | sb3/a2c-AsteroidsNoFrameskip-v4 | null | [
"stable-baselines3",
"AsteroidsNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:47:28+00:00 | [] | [] | TAGS
#stable-baselines3 #AsteroidsNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing AsteroidsNoFrameskip-v4
This is a trained model of a A2C agent playing AsteroidsNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents include... | [
"# A2C Agent playing AsteroidsNoFrameskip-v4\nThis is a trained model of a A2C agent playing AsteroidsNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained age... | [
"TAGS\n#stable-baselines3 #AsteroidsNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing AsteroidsNoFrameskip-v4\nThis is a trained model of a A2C agent playing AsteroidsNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **LunarLanderContinuous-v2**
This is a trained model of a **A2C** agent playing **LunarLanderContinuous-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["LunarLanderContinuous-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLanderContinuous-... | sb3/a2c-LunarLanderContinuous-v2 | null | [
"stable-baselines3",
"LunarLanderContinuous-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T14:48:22+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing LunarLanderContinuous-v2
This is a trained model of a A2C agent playing LunarLanderContinuous-v2
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# A2C Agent playing LunarLanderContinuous-v2\nThis is a trained model of a A2C agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing LunarLanderContinuous-v2\nThis is a trained model of a A2C agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-base-combined-squad1-aqa-and-newsqa-1epoch
This model is a fine-tuned version of [stevemobs/deberta-base-combined-squad1... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "deberta-base-combined-squad1-aqa-and-newsqa-1epoch", "results": []}]} | stevemobs/deberta-base-combined-squad1-aqa-and-newsqa-1epoch | null | [
"transformers",
"pytorch",
"tensorboard",
"deberta",
"question-answering",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T14:53:40+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #deberta #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us
| deberta-base-combined-squad1-aqa-and-newsqa-1epoch
==================================================
This model is a fine-tuned version of stevemobs/deberta-base-combined-squad1-aqa on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6851
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\_size: 12\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #deberta #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-timit-demo-google-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/face... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-timit-demo-google-colab", "results": []}]} | awghuku/wav2vec2-base-timit-demo-google-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T15:03:09+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-timit-demo-google-colab
=====================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4732
* Wer: 0.3300
Model description
-----------------
More information needed
Intend... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8... |
text2text-generation | transformers |
# MVP-multi-task
The MVP-multi-task model was proposed in [**MVP: Multi-task Supervised Pre-training for Natural Language Generation**](https://arxiv.org/abs/2206.12131) by Tianyi Tang, Junyi Li, Wayne Xin Zhao and Ji-Rong Wen.
The detailed information and instructions can be found [https://github.com/RUCAIBox/MVP](h... | {"language": ["en"], "license": "apache-2.0", "tags": ["text-generation", "text2text-generation", "summarization", "conversational"], "pipeline_tag": "text2text-generation", "widget": [{"text": "Summarize: You may want to stick it to your boss and leave your job, but don't do it if these are your reasons.", "example_ti... | RUCAIBox/mvp-multi-task | null | [
"transformers",
"pytorch",
"mvp",
"text-generation",
"text2text-generation",
"summarization",
"conversational",
"en",
"arxiv:2206.12131",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T15:04:07+00:00 | [
"2206.12131"
] | [
"en"
] | TAGS
#transformers #pytorch #mvp #text-generation #text2text-generation #summarization #conversational #en #arxiv-2206.12131 #license-apache-2.0 #endpoints_compatible #region-us
|
# MVP-multi-task
The MVP-multi-task model was proposed in MVP: Multi-task Supervised Pre-training for Natural Language Generation by Tianyi Tang, Junyi Li, Wayne Xin Zhao and Ji-Rong Wen.
The detailed information and instructions can be found URL
## Model Description
MVP-multi-task is a prompt-based model that MVP i... | [
"# MVP-multi-task\nThe MVP-multi-task model was proposed in MVP: Multi-task Supervised Pre-training for Natural Language Generation by Tianyi Tang, Junyi Li, Wayne Xin Zhao and Ji-Rong Wen.\n\nThe detailed information and instructions can be found URL",
"## Model Description\nMVP-multi-task is a prompt-based mode... | [
"TAGS\n#transformers #pytorch #mvp #text-generation #text2text-generation #summarization #conversational #en #arxiv-2206.12131 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# MVP-multi-task\nThe MVP-multi-task model was proposed in MVP: Multi-task Supervised Pre-training for Natural Language Generati... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **BipedalWalker-v3**
This is a trained model of a **A2C** agent playing **BipedalWalker-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines... | {"library_name": "stable-baselines3", "tags": ["BipedalWalker-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | sb3/a2c-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:05:45+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing BipedalWalker-v3
This is a trained model of a A2C agent playing BipedalWalker-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (... | [
"# A2C Agent playing BipedalWalker-v3\nThis is a trained model of a A2C agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included."... | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing BipedalWalker-v3\nThis is a trained model of a A2C agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fra... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | OneFly/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T15:08:58+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2108
* Accuracy: 0.928
* F1: 0.9280
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **QbertNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **QbertNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Bas... | {"library_name": "stable-baselines3", "tags": ["QbertNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "QbertNoFrameskip-v4", "type... | sb3/a2c-QbertNoFrameskip-v4 | null | [
"stable-baselines3",
"QbertNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:22:59+00:00 | [] | [] | TAGS
#stable-baselines3 #QbertNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing QbertNoFrameskip-v4
This is a trained model of a A2C agent playing QbertNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## U... | [
"# A2C Agent playing QbertNoFrameskip-v4\nThis is a trained model of a A2C agent playing QbertNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents incl... | [
"TAGS\n#stable-baselines3 #QbertNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing QbertNoFrameskip-v4\nThis is a trained model of a A2C agent playing QbertNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **BipedalWalkerHardcore-v3**
This is a trained model of a **A2C** agent playing **BipedalWalkerHardcore-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["BipedalWalkerHardcore-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalkerHardcore-... | sb3/a2c-BipedalWalkerHardcore-v3 | null | [
"stable-baselines3",
"BipedalWalkerHardcore-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:23:54+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalkerHardcore-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing BipedalWalkerHardcore-v3
This is a trained model of a A2C agent playing BipedalWalkerHardcore-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# A2C Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a A2C agent playing BipedalWalkerHardcore-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #BipedalWalkerHardcore-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a A2C agent playing BipedalWalkerHardcore-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **Walker2DBulletEnv-v0**
This is a trained model of a **A2C** agent playing **Walker2DBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable B... | {"library_name": "stable-baselines3", "tags": ["Walker2DBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2DBulletEnv-v0", "ty... | sb3/a2c-Walker2DBulletEnv-v0 | null | [
"stable-baselines3",
"Walker2DBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:41:17+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing Walker2DBulletEnv-v0
This is a trained model of a A2C agent playing Walker2DBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
##... | [
"# A2C Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a A2C agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents in... | [
"TAGS\n#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a A2C agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
reinforcement-learning | stable-baselines3 |
# **A2C** Agent playing **BeamRiderNoFrameskip-v4**
This is a trained model of a **A2C** agent playing **BeamRiderNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for St... | {"library_name": "stable-baselines3", "tags": ["BeamRiderNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BeamRiderNoFrameskip-v4... | sb3/a2c-BeamRiderNoFrameskip-v4 | null | [
"stable-baselines3",
"BeamRiderNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:42:23+00:00 | [] | [] | TAGS
#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# A2C Agent playing BeamRiderNoFrameskip-v4
This is a trained model of a A2C agent playing BeamRiderNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents include... | [
"# A2C Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a A2C agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained age... | [
"TAGS\n#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# A2C Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a A2C agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **Humanoid-v3**
This is a trained model of a **SAC** agent playing **Humanoid-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforc... | {"library_name": "stable-baselines3", "tags": ["Humanoid-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Humanoid-v3", "type": "Humanoid-v3"... | sb3/sac-Humanoid-v3 | null | [
"stable-baselines3",
"Humanoid-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:44:09+00:00 | [] | [] | TAGS
#stable-baselines3 #Humanoid-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing Humanoid-v3
This is a trained model of a SAC agent playing Humanoid-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 R... | [
"# SAC Agent playing Humanoid-v3\nThis is a trained model of a SAC agent playing Humanoid-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Us... | [
"TAGS\n#stable-baselines3 #Humanoid-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing Humanoid-v3\nThis is a trained model of a SAC agent playing Humanoid-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **Walker2d-v3**
This is a trained model of a **SAC** agent playing **Walker2d-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforc... | {"library_name": "stable-baselines3", "tags": ["Walker2d-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2d-v3", "type": "Walker2d-v3"... | sb3/sac-Walker2d-v3 | null | [
"stable-baselines3",
"Walker2d-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:45:31+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2d-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing Walker2d-v3
This is a trained model of a SAC agent playing Walker2d-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 R... | [
"# SAC Agent playing Walker2d-v3\nThis is a trained model of a SAC agent playing Walker2d-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Us... | [
"TAGS\n#stable-baselines3 #Walker2d-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing Walker2d-v3\nThis is a trained model of a SAC agent playing Walker2d-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **HalfCheetah-v3**
This is a trained model of a **SAC** agent playing **HalfCheetah-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
re... | {"library_name": "stable-baselines3", "tags": ["HalfCheetah-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetah-v3", "type": "HalfCh... | sb3/sac-HalfCheetah-v3 | null | [
"stable-baselines3",
"HalfCheetah-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:46:24+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing HalfCheetah-v3
This is a trained model of a SAC agent playing HalfCheetah-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with... | [
"# SAC Agent playing HalfCheetah-v3\nThis is a trained model of a SAC agent playing HalfCheetah-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing HalfCheetah-v3\nThis is a trained model of a SAC agent playing HalfCheetah-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **AntBulletEnv-v0**
This is a trained model of a **SAC** agent playing **AntBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
... | {"library_name": "stable-baselines3", "tags": ["AntBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "AntB... | sb3/sac-AntBulletEnv-v0 | null | [
"stable-baselines3",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:47:23+00:00 | [] | [] | TAGS
#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing AntBulletEnv-v0
This is a trained model of a SAC agent playing AntBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (wi... | [
"# SAC Agent playing AntBulletEnv-v0\nThis is a trained model of a SAC agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing AntBulletEnv-v0\nThis is a trained model of a SAC agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framew... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **Swimmer-v3**
This is a trained model of a **SAC** agent playing **Swimmer-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcem... | {"library_name": "stable-baselines3", "tags": ["Swimmer-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Swimmer-v3", "type": "Swimmer-v3"}, ... | sb3/sac-Swimmer-v3 | null | [
"stable-baselines3",
"Swimmer-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:48:31+00:00 | [] | [] | TAGS
#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing Swimmer-v3
This is a trained model of a SAC agent playing Swimmer-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL ... | [
"# SAC Agent playing Swimmer-v3\nThis is a trained model of a SAC agent playing Swimmer-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usag... | [
"TAGS\n#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing Swimmer-v3\nThis is a trained model of a SAC agent playing Swimmer-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **Hopper-v3**
This is a trained model of a **SAC** agent playing **Hopper-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcemen... | {"library_name": "stable-baselines3", "tags": ["Hopper-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Hopper-v3", "type": "Hopper-v3"}, "me... | sb3/sac-Hopper-v3 | null | [
"stable-baselines3",
"Hopper-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:49:34+00:00 | [] | [] | TAGS
#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing Hopper-v3
This is a trained model of a SAC agent playing Hopper-v3
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zo... | [
"# SAC Agent playing Hopper-v3\nThis is a trained model of a SAC agent playing Hopper-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## Usage ... | [
"TAGS\n#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing Hopper-v3\nThis is a trained model of a SAC agent playing Hopper-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Bas... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **ReacherBulletEnv-v0**
This is a trained model of a **SAC** agent playing **ReacherBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Bas... | {"library_name": "stable-baselines3", "tags": ["ReacherBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ReacherBulletEnv-v0", "type... | sb3/sac-ReacherBulletEnv-v0 | null | [
"stable-baselines3",
"ReacherBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:50:33+00:00 | [] | [] | TAGS
#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing ReacherBulletEnv-v0
This is a trained model of a SAC agent playing ReacherBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## U... | [
"# SAC Agent playing ReacherBulletEnv-v0\nThis is a trained model of a SAC agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents incl... | [
"TAGS\n#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing ReacherBulletEnv-v0\nThis is a trained model of a SAC agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **HopperBulletEnv-v0**
This is a trained model of a **SAC** agent playing **HopperBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Basel... | {"library_name": "stable-baselines3", "tags": ["HopperBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HopperBulletEnv-v0", "type":... | sb3/sac-HopperBulletEnv-v0 | null | [
"stable-baselines3",
"HopperBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:51:34+00:00 | [] | [] | TAGS
#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing HopperBulletEnv-v0
This is a trained model of a SAC agent playing HopperBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usa... | [
"# SAC Agent playing HopperBulletEnv-v0\nThis is a trained model of a SAC agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents includ... | [
"TAGS\n#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing HopperBulletEnv-v0\nThis is a trained model of a SAC agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **HalfCheetahBulletEnv-v0**
This is a trained model of a **SAC** agent playing **HalfCheetahBulletEnv-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for St... | {"library_name": "stable-baselines3", "tags": ["HalfCheetahBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetahBulletEnv-v0... | sb3/sac-HalfCheetahBulletEnv-v0 | null | [
"stable-baselines3",
"HalfCheetahBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:52:40+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing HalfCheetahBulletEnv-v0
This is a trained model of a SAC agent playing HalfCheetahBulletEnv-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents include... | [
"# SAC Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a SAC agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained age... | [
"TAGS\n#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a SAC agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **LunarLanderContinuous-v2**
This is a trained model of a **SAC** agent playing **LunarLanderContinuous-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for ... | {"library_name": "stable-baselines3", "tags": ["LunarLanderContinuous-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLanderContinuous-... | sb3/sac-LunarLanderContinuous-v2 | null | [
"stable-baselines3",
"LunarLanderContinuous-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T15:54:00+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing LunarLanderContinuous-v2
This is a trained model of a SAC agent playing LunarLanderContinuous-v2
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents inclu... | [
"# SAC Agent playing LunarLanderContinuous-v2\nThis is a trained model of a SAC agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained a... | [
"TAGS\n#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing LunarLanderContinuous-v2\nThis is a trained model of a SAC agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | vortixhead/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T15:55:10+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2140
* Accuracy: 0.924
* F1: 0.9241
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.