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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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="jcastanyo/q-FrozenLake-v1-8x8-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional at... | {"tags": ["FrozenLake-v1-8x8-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-8x8-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-8x8-no_slippery", "type": ... | jcastanyo/q-FrozenLake-v1-8x8-noSlippery | null | [
"FrozenLake-v1-8x8-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-02T15:57:16+00:00 | [] | [] | TAGS
#FrozenLake-v1-8x8-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-v1-8x8-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"
] |
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. -->
# urdu-asr
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "urdu-asr", "results": []}]} | Zaafir/urdu-asr | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T16:03:00+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| urdu-asr
========
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: 1.5640
* Wer: 0.8546
Model description
-----------------
More information needed
Intended uses & limitations
---------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\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... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **BipedalWalker-v3**
This is a trained model of a **SAC** 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": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | sb3/sac-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:04:41+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing BipedalWalker-v3
This is a trained model of a SAC 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 (... | [
"# SAC Agent playing BipedalWalker-v3\nThis is a trained model of a SAC 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",
"# SAC Agent playing BipedalWalker-v3\nThis is a trained model of a SAC agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fra... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **BipedalWalkerHardcore-v3**
This is a trained model of a **SAC** 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": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalkerHardcore-... | sb3/sac-BipedalWalkerHardcore-v3 | null | [
"stable-baselines3",
"BipedalWalkerHardcore-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:05:41+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalkerHardcore-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing BipedalWalkerHardcore-v3
This is a trained model of a SAC 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... | [
"# SAC Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a SAC 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",
"# SAC Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a SAC agent playing BipedalWalkerHardcore-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **Walker2DBulletEnv-v0**
This is a trained model of a **SAC** 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": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2DBulletEnv-v0", "ty... | sb3/sac-Walker2DBulletEnv-v0 | null | [
"stable-baselines3",
"Walker2DBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:06:49+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing Walker2DBulletEnv-v0
This is a trained model of a SAC 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.
##... | [
"# SAC Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a SAC 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",
"# SAC Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a SAC agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **MountainCarContinuous-v0**
This is a trained model of a **SAC** 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": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCarContinuous-... | sb3/sac-MountainCarContinuous-v0 | null | [
"stable-baselines3",
"MountainCarContinuous-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:07:55+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing MountainCarContinuous-v0
This is a trained model of a SAC 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... | [
"# SAC Agent playing MountainCarContinuous-v0\nThis is a trained model of a SAC 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",
"# SAC Agent playing MountainCarContinuous-v0\nThis is a trained model of a SAC agent playing MountainCarContinuous-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **Ant-v3**
This is a trained model of a **SAC** 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": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Ant-v3", "type": "Ant-v3"}, "metrics": [... | sb3/sac-Ant-v3 | null | [
"stable-baselines3",
"Ant-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:08:40+00:00 | [] | [] | TAGS
#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing Ant-v3
This is a trained model of a SAC 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... | [
"# SAC Agent playing Ant-v3\nThis is a trained model of a SAC 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",
"# SAC Agent playing Ant-v3\nThis is a trained model of a SAC 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 |
# **ARS** Agent playing **Walker2d-v3**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2d-v3", "type": "Walker2d-v3"... | sb3/ars-Walker2d-v3 | null | [
"stable-baselines3",
"Walker2d-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:09:37+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2d-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing Walker2d-v3
This is a trained model of a ARS 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... | [
"# ARS Agent playing Walker2d-v3\nThis is a trained model of a ARS 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",
"# ARS Agent playing Walker2d-v3\nThis is a trained model of a ARS 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 |
# **ARS** Agent playing **MountainCar-v0**
This is a trained model of a **ARS** 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 Baselines3
re... | {"library_name": "stable-baselines3", "tags": ["MountainCar-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCar-v0", "type": "Mounta... | sb3/ars-MountainCar-v0 | null | [
"stable-baselines3",
"MountainCar-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:10:26+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCar-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing MountainCar-v0
This is a trained model of a ARS 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 (with... | [
"# ARS Agent playing MountainCar-v0\nThis is a trained model of a ARS 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",
"# ARS Agent playing MountainCar-v0\nThis is a trained model of a ARS agent playing MountainCar-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework... |
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/1504854177993744386/k8Tb... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/rauschermri/1654193526819/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/rauschermri | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T16:12:12+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Alexander Rauscher
@rauschermri
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 | 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="jcastanyo/q-FrozenLake-v1-4x4-Slippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attr... | {"tags": ["FrozenLake-v1-4x4", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-Slippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4", "type": "FrozenLake-v1-4x4"}, "met... | jcastanyo/q-FrozenLake-v1-4x4-Slippery | null | [
"FrozenLake-v1-4x4",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-02T16:17:38+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4 #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 #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"
] |
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-it-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-it-colab", "results": []}]} | gciaffoni/wav2vec2-large-xls-r-300m-it-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T16:17:58+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-it-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: 0.1660
* Wer: 0.1648
Model description
-----------------
More information needed... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\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\\_step... | [
"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... |
reinforcement-learning | stable-baselines3 |
# **ARS** Agent playing **Acrobot-v1**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Acrobot-v1", "type": "Acrobot-v1"}, ... | sb3/ars-Acrobot-v1 | null | [
"stable-baselines3",
"Acrobot-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:21:26+00:00 | [] | [] | TAGS
#stable-baselines3 #Acrobot-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing Acrobot-v1
This is a trained model of a ARS 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 ... | [
"# ARS Agent playing Acrobot-v1\nThis is a trained model of a ARS 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",
"# ARS Agent playing Acrobot-v1\nThis is a trained model of a ARS agent playing Acrobot-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
reinforcement-learning | stable-baselines3 |
# **ARS** Agent playing **HalfCheetah-v3**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetah-v3", "type": "HalfCh... | sb3/ars-HalfCheetah-v3 | null | [
"stable-baselines3",
"HalfCheetah-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:22:11+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing HalfCheetah-v3
This is a trained model of a ARS 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... | [
"# ARS Agent playing HalfCheetah-v3\nThis is a trained model of a ARS 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",
"# ARS Agent playing HalfCheetah-v3\nThis is a trained model of a ARS 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 |
# **ARS** Agent playing **Swimmer-v3**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Swimmer-v3", "type": "Swimmer-v3"}, ... | sb3/ars-Swimmer-v3 | null | [
"stable-baselines3",
"Swimmer-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:22:56+00:00 | [] | [] | TAGS
#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing Swimmer-v3
This is a trained model of a ARS 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 ... | [
"# ARS Agent playing Swimmer-v3\nThis is a trained model of a ARS 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",
"# ARS Agent playing Swimmer-v3\nThis is a trained model of a ARS 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 |
# **ARS** Agent playing **Hopper-v3**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Hopper-v3", "type": "Hopper-v3"}, "me... | sb3/ars-Hopper-v3 | null | [
"stable-baselines3",
"Hopper-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:23:48+00:00 | [] | [] | TAGS
#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing Hopper-v3
This is a trained model of a ARS 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... | [
"# ARS Agent playing Hopper-v3\nThis is a trained model of a ARS 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",
"# ARS Agent playing Hopper-v3\nThis is a trained model of a ARS 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 |
# **ARS** Agent playing **Pendulum-v1**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pendulum-v1", "type": "Pendulum-v1"... | sb3/ars-Pendulum-v1 | null | [
"stable-baselines3",
"Pendulum-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:24:44+00:00 | [] | [] | TAGS
#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing Pendulum-v1
This is a trained model of a ARS 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... | [
"# ARS Agent playing Pendulum-v1\nThis is a trained model of a ARS 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",
"# ARS Agent playing Pendulum-v1\nThis is a trained model of a ARS 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 | stable-baselines3 |
# **ARS** Agent playing **LunarLanderContinuous-v2**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLanderContinuous-... | sb3/ars-LunarLanderContinuous-v2 | null | [
"stable-baselines3",
"LunarLanderContinuous-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:25:29+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing LunarLanderContinuous-v2
This is a trained model of a ARS 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... | [
"# ARS Agent playing LunarLanderContinuous-v2\nThis is a trained model of a ARS 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",
"# ARS Agent playing LunarLanderContinuous-v2\nThis is a trained model of a ARS agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **ARS** Agent playing **MountainCarContinuous-v0**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCarContinuous-... | sb3/ars-MountainCarContinuous-v0 | null | [
"stable-baselines3",
"MountainCarContinuous-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:26:16+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing MountainCarContinuous-v0
This is a trained model of a ARS 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... | [
"# ARS Agent playing MountainCarContinuous-v0\nThis is a trained model of a ARS 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",
"# ARS Agent playing MountainCarContinuous-v0\nThis is a trained model of a ARS agent playing MountainCarContinuous-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **ARS** Agent playing **CartPole-v1**
This is a trained model of a **ARS** 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
reinforc... | {"library_name": "stable-baselines3", "tags": ["CartPole-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"... | sb3/ars-CartPole-v1 | null | [
"stable-baselines3",
"CartPole-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:30:01+00:00 | [] | [] | TAGS
#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing CartPole-v1
This is a trained model of a ARS 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 SB3 R... | [
"# ARS Agent playing CartPole-v1\nThis is a trained model of a ARS 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.",
"## Us... | [
"TAGS\n#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# ARS Agent playing CartPole-v1\nThis is a trained model of a ARS agent playing CartPole-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
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-common-voice-50p-persian-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-common-voice-50p-persian-colab", "results": []}]} | zoha/wav2vec2-base-common-voice-50p-persian-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T16:30:52+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-common-voice-50p-persian-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: 1.0939
* Wer: 0.6537
Model description
-----------------
More information n... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7.5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 1\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\\_step... | [
"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: 7.5e-05\n* train\\_batch\\_size: ... |
reinforcement-learning | stable-baselines3 |
# **ARS** Agent playing **Ant-v3**
This is a trained model of a **ARS** 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": "ARS", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Ant-v3", "type": "Ant-v3"}, "metrics": [... | sb3/ars-Ant-v3 | null | [
"stable-baselines3",
"Ant-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:47:10+00:00 | [] | [] | TAGS
#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# ARS Agent playing Ant-v3
This is a trained model of a ARS 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... | [
"# ARS Agent playing Ant-v3\nThis is a trained model of a ARS 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",
"# ARS Agent playing Ant-v3\nThis is a trained model of a ARS 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 |
# **DQN** Agent playing **PongNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PongNoFrameskip-v4", "type":... | sb3/dqn-PongNoFrameskip-v4 | null | [
"stable-baselines3",
"PongNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:48:01+00:00 | [] | [] | TAGS
#stable-baselines3 #PongNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing PongNoFrameskip-v4
This is a trained model of a DQN 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... | [
"# DQN Agent playing PongNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing PongNoFrameskip-v4\nThis is a trained model of a DQN agent playing PongNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
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="jcastanyo/q-FrozenLake-v1-4x4-Slippery-v2", filename="q-learning.pkl")
# Don't forget to check if you need to add additional a... | {"tags": ["FrozenLake-v1-4x4", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-Slippery-v2", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4", "type": "FrozenLake-v1-4x4"}, "... | jcastanyo/q-FrozenLake-v1-4x4-Slippery-v2 | null | [
"FrozenLake-v1-4x4",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-02T16:49:04+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4 #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 #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 |
# **DQN** Agent playing **LunarLander-v2**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | sb3/dqn-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T16:49:10+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing LunarLander-v2
This is a trained model of a DQN 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... | [
"# DQN Agent playing LunarLander-v2\nThis is a trained model of a DQN 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",
"# DQN Agent playing LunarLander-v2\nThis is a trained model of a DQN agent playing LunarLander-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework... |
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. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}]} | victorlee071200/distilbert-base-uncased-finetuned-squad | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T16:51:00+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-squad
=======================================
This model is a fine-tuned version of distilbert-base-uncased on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1458
Model description
-----------------
More information needed
Intended uses ... | [
"### 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: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #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: 2e-05\n* train\\_batch\\_s... |
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. -->
# UrduAudio2Text
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "UrduAudio2Text", "results": []}]} | Umer4/UrduAudio2Text | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T16:52:38+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| UrduAudio2Text
==============
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: 1.4978
* Wer: 0.8376
Model description
-----------------
More information needed
Intended uses & limitations
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\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... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **Acrobot-v1**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Acrobot-v1", "type": "Acrobot-v1"}, ... | sb3/dqn-Acrobot-v1 | null | [
"stable-baselines3",
"Acrobot-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:06:27+00:00 | [] | [] | TAGS
#stable-baselines3 #Acrobot-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing Acrobot-v1
This is a trained model of a DQN 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 ... | [
"# DQN Agent playing Acrobot-v1\nThis is a trained model of a DQN 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",
"# DQN Agent playing Acrobot-v1\nThis is a trained model of a DQN agent playing Acrobot-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
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="jcastanyo/q-FrozenLake-v1-4x4-Slippery-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional a... | {"tags": ["FrozenLake-v1-4x4", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-Slippery-v3", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4", "type": "FrozenLake-v1-4x4"}, "... | jcastanyo/q-FrozenLake-v1-4x4-Slippery-v3 | null | [
"FrozenLake-v1-4x4",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-02T17:13:51+00:00 | [] | [] | TAGS
#FrozenLake-v1-4x4 #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 #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 |
# **DQN** Agent playing **EnduroNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "EnduroNoFrameskip-v4", "ty... | sb3/dqn-EnduroNoFrameskip-v4 | null | [
"stable-baselines3",
"EnduroNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:17:01+00:00 | [] | [] | TAGS
#stable-baselines3 #EnduroNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing EnduroNoFrameskip-v4
This is a trained model of a DQN 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.
##... | [
"# DQN Agent playing EnduroNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing EnduroNoFrameskip-v4\nThis is a trained model of a DQN agent playing EnduroNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **RoadRunnerNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "RoadRunnerNoFrameskip-... | sb3/dqn-RoadRunnerNoFrameskip-v4 | null | [
"stable-baselines3",
"RoadRunnerNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:21:32+00:00 | [] | [] | TAGS
#stable-baselines3 #RoadRunnerNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing RoadRunnerNoFrameskip-v4
This is a trained model of a DQN 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... | [
"# DQN Agent playing RoadRunnerNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing RoadRunnerNoFrameskip-v4\nThis is a trained model of a DQN agent playing RoadRunnerNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | sb3/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"has_space",
"region:us"
] | null | 2022-06-02T17:22:16+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #has_space #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN 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... | [
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **BreakoutNoFrameskip-v4**
This is a trained model of a **DQN** 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 Stab... | {"library_name": "stable-baselines3", "tags": ["BreakoutNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BreakoutNoFrameskip-v4",... | sb3/dqn-BreakoutNoFrameskip-v4 | null | [
"stable-baselines3",
"BreakoutNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:23:12+00:00 | [] | [] | TAGS
#stable-baselines3 #BreakoutNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing BreakoutNoFrameskip-v4
This is a trained model of a DQN 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 included.... | [
"# DQN Agent playing BreakoutNoFrameskip-v4\nThis is a trained model of a DQN 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 agent... | [
"TAGS\n#stable-baselines3 #BreakoutNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing BreakoutNoFrameskip-v4\nThis is a trained model of a DQN agent playing BreakoutNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SeaquestNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SeaquestNoFrameskip-v4",... | sb3/dqn-SeaquestNoFrameskip-v4 | null | [
"stable-baselines3",
"SeaquestNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:24:51+00:00 | [] | [] | TAGS
#stable-baselines3 #SeaquestNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SeaquestNoFrameskip-v4
This is a trained model of a DQN 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.... | [
"# DQN Agent playing SeaquestNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing SeaquestNoFrameskip-v4\nThis is a trained model of a DQN agent playing SeaquestNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **AsteroidsNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AsteroidsNoFrameskip-v4... | sb3/dqn-AsteroidsNoFrameskip-v4 | null | [
"stable-baselines3",
"AsteroidsNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:26:18+00:00 | [] | [] | TAGS
#stable-baselines3 #AsteroidsNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing AsteroidsNoFrameskip-v4
This is a trained model of a DQN 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... | [
"# DQN Agent playing AsteroidsNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing AsteroidsNoFrameskip-v4\nThis is a trained model of a DQN agent playing AsteroidsNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **QbertNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "QbertNoFrameskip-v4", "type... | sb3/dqn-QbertNoFrameskip-v4 | null | [
"stable-baselines3",
"QbertNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:27:25+00:00 | [] | [] | TAGS
#stable-baselines3 #QbertNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing QbertNoFrameskip-v4
This is a trained model of a DQN 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... | [
"# DQN Agent playing QbertNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing QbertNoFrameskip-v4\nThis is a trained model of a DQN agent playing QbertNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **BeamRiderNoFrameskip-v4**
This is a trained model of a **DQN** 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": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BeamRiderNoFrameskip-v4... | sb3/dqn-BeamRiderNoFrameskip-v4 | null | [
"stable-baselines3",
"BeamRiderNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:28:20+00:00 | [] | [] | TAGS
#stable-baselines3 #BeamRiderNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing BeamRiderNoFrameskip-v4
This is a trained model of a DQN 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... | [
"# DQN Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a DQN 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",
"# DQN Agent playing BeamRiderNoFrameskip-v4\nThis is a trained model of a DQN agent playing BeamRiderNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
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/1171375301768744961/QZbL... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/davemomi/1654194627703/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/davemomi | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T17:29:46+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Davide Momi
@davemomi
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 |
# **DQN** Agent playing **CartPole-v1**
This is a trained model of a **DQN** 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
reinforc... | {"library_name": "stable-baselines3", "tags": ["CartPole-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"... | sb3/dqn-CartPole-v1 | null | [
"stable-baselines3",
"CartPole-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:30:35+00:00 | [] | [] | TAGS
#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing CartPole-v1
This is a trained model of a DQN 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 SB3 R... | [
"# DQN Agent playing CartPole-v1\nThis is a trained model of a DQN 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.",
"## Us... | [
"TAGS\n#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing CartPole-v1\nThis is a trained model of a DQN agent playing CartPole-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stab... |
text-generation | transformers |
# BOTHALTEROUT
This model is a fine-tuned version of [GPT-2](https://huggingface.co/gpt2) using 21,832 tweets from 12 twitter users with very strong opinions about the United States Men's National Team.
## Limitations and bias
The model has all [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#li... | {"license": "mit", "widget": [{"text": "Gregg Berhalter"}, {"text": "The USMNT won't win the World Cup"}, {"text": "The Soccer Media in this country"}, {"text": "Ball don't"}, {"text": "This lineup"}], "model-index": [{"name": "BERFALTER", "results": []}]} | etmckinley/BOTHALTEROUT | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T17:32:15+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# BOTHALTEROUT
This model is a fine-tuned version of GPT-2 using 21,832 tweets from 12 twitter users with very strong opinions about the United States Men's National Team.
## Limitations and bias
The model has all the same limitations and bias as GPT-2.
Additionally, BOTHALTEROUT can create some problematic result... | [
"# BOTHALTEROUT\n\nThis model is a fine-tuned version of GPT-2 using 21,832 tweets from 12 twitter users with very strong opinions about the United States Men's National Team.",
"## Limitations and bias\n\nThe model has all the same limitations and bias as GPT-2.\n\nAdditionally, BOTHALTEROUT can create some prob... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# BOTHALTEROUT\n\nThis model is a fine-tuned version of GPT-2 using 21,832 tweets from 12 twitter users with very strong opinions about the United ... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **Humanoid-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Humanoid-v3", "type": "Humanoid-v3"... | sb3/tqc-Humanoid-v3 | null | [
"stable-baselines3",
"Humanoid-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:47:46+00:00 | [] | [] | TAGS
#stable-baselines3 #Humanoid-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing Humanoid-v3
This is a trained model of a TQC 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... | [
"# TQC Agent playing Humanoid-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing Humanoid-v3\nThis is a trained model of a TQC 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 |
# **TQC** Agent playing **PandaPickAndPlace-v1**
This is a trained model of a **TQC** agent playing **PandaPickAndPlace-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 B... | {"library_name": "stable-baselines3", "tags": ["PandaPickAndPlace-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaPickAndPlace-v1", "ty... | sb3/tqc-PandaPickAndPlace-v1 | null | [
"stable-baselines3",
"PandaPickAndPlace-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"arxiv:2106.13687",
"model-index",
"region:us"
] | null | 2022-06-02T17:49:00+00:00 | [
"2106.13687"
] | [] | TAGS
#stable-baselines3 #PandaPickAndPlace-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us
|
# TQC Agent playing PandaPickAndPlace-v1
This is a trained model of a TQC agent playing PandaPickAndPlace-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.
##... | [
"# TQC Agent playing PandaPickAndPlace-v1\nThis is a trained model of a TQC agent playing PandaPickAndPlace-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 in... | [
"TAGS\n#stable-baselines3 #PandaPickAndPlace-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us \n",
"# TQC Agent playing PandaPickAndPlace-v1\nThis is a trained model of a TQC agent playing PandaPickAndPlace-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **Walker2d-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2d-v3", "type": "Walker2d-v3"... | sb3/tqc-Walker2d-v3 | null | [
"stable-baselines3",
"Walker2d-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:50:57+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2d-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing Walker2d-v3
This is a trained model of a TQC 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... | [
"# TQC Agent playing Walker2d-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing Walker2d-v3\nThis is a trained model of a TQC 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 |
# **TQC** Agent playing **HalfCheetah-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetah-v3", "type": "HalfCh... | sb3/tqc-HalfCheetah-v3 | null | [
"stable-baselines3",
"HalfCheetah-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:51:52+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetah-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing HalfCheetah-v3
This is a trained model of a TQC 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... | [
"# TQC Agent playing HalfCheetah-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing HalfCheetah-v3\nThis is a trained model of a TQC 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 |
# **TQC** Agent playing **AntBulletEnv-v0**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "AntB... | sb3/tqc-AntBulletEnv-v0 | null | [
"stable-baselines3",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:52:46+00:00 | [] | [] | TAGS
#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing AntBulletEnv-v0
This is a trained model of a TQC 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... | [
"# TQC Agent playing AntBulletEnv-v0\nThis is a trained model of a TQC 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",
"# TQC Agent playing AntBulletEnv-v0\nThis is a trained model of a TQC 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 |
# **TQC** Agent playing **Swimmer-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Swimmer-v3", "type": "Swimmer-v3"}, ... | sb3/tqc-Swimmer-v3 | null | [
"stable-baselines3",
"Swimmer-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:53:58+00:00 | [] | [] | TAGS
#stable-baselines3 #Swimmer-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing Swimmer-v3
This is a trained model of a TQC 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 ... | [
"# TQC Agent playing Swimmer-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing Swimmer-v3\nThis is a trained model of a TQC 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 |
# **TQC** Agent playing **Hopper-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Hopper-v3", "type": "Hopper-v3"}, "me... | sb3/tqc-Hopper-v3 | null | [
"stable-baselines3",
"Hopper-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:54:56+00:00 | [] | [] | TAGS
#stable-baselines3 #Hopper-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing Hopper-v3
This is a trained model of a TQC 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... | [
"# TQC Agent playing Hopper-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing Hopper-v3\nThis is a trained model of a TQC 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 |
# **TQC** Agent playing **ReacherBulletEnv-v0**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ReacherBulletEnv-v0", "type... | sb3/tqc-ReacherBulletEnv-v0 | null | [
"stable-baselines3",
"ReacherBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:56:01+00:00 | [] | [] | TAGS
#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing ReacherBulletEnv-v0
This is a trained model of a TQC 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... | [
"# TQC Agent playing ReacherBulletEnv-v0\nThis is a trained model of a TQC 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",
"# TQC Agent playing ReacherBulletEnv-v0\nThis is a trained model of a TQC agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **HopperBulletEnv-v0**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HopperBulletEnv-v0", "type":... | sb3/tqc-HopperBulletEnv-v0 | null | [
"stable-baselines3",
"HopperBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:57:00+00:00 | [] | [] | TAGS
#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing HopperBulletEnv-v0
This is a trained model of a TQC 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... | [
"# TQC Agent playing HopperBulletEnv-v0\nThis is a trained model of a TQC 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",
"# TQC Agent playing HopperBulletEnv-v0\nThis is a trained model of a TQC agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **HalfCheetahBulletEnv-v0**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetahBulletEnv-v0... | sb3/tqc-HalfCheetahBulletEnv-v0 | null | [
"stable-baselines3",
"HalfCheetahBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T17:58:07+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing HalfCheetahBulletEnv-v0
This is a trained model of a TQC 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... | [
"# TQC Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a TQC 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",
"# TQC Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a TQC agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL ... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **PandaStack-v1**
This is a trained model of a **TQC** agent playing **PandaStack-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": ["PandaStack-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaStack-v1", "type": "PandaSta... | sb3/tqc-PandaStack-v1 | null | [
"stable-baselines3",
"PandaStack-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"arxiv:2106.13687",
"model-index",
"region:us"
] | null | 2022-06-02T17:59:20+00:00 | [
"2106.13687"
] | [] | TAGS
#stable-baselines3 #PandaStack-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us
|
# TQC Agent playing PandaStack-v1
This is a trained model of a TQC agent playing PandaStack-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... | [
"# TQC Agent playing PandaStack-v1\nThis is a trained model of a TQC agent playing PandaStack-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 #PandaStack-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us \n",
"# TQC Agent playing PandaStack-v1\nThis is a trained model of a TQC agent playing PandaStack-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **PandaSlide-v1**
This is a trained model of a **TQC** agent playing **PandaSlide-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": ["PandaSlide-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaSlide-v1", "type": "PandaSli... | sb3/tqc-PandaSlide-v1 | null | [
"stable-baselines3",
"PandaSlide-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"arxiv:2106.13687",
"model-index",
"region:us"
] | null | 2022-06-02T18:01:23+00:00 | [
"2106.13687"
] | [] | TAGS
#stable-baselines3 #PandaSlide-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us
|
# TQC Agent playing PandaSlide-v1
This is a trained model of a TQC agent playing PandaSlide-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... | [
"# TQC Agent playing PandaSlide-v1\nThis is a trained model of a TQC agent playing PandaSlide-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 #PandaSlide-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us \n",
"# TQC Agent playing PandaSlide-v1\nThis is a trained model of a TQC agent playing PandaSlide-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **LunarLanderContinuous-v2**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLanderContinuous-... | sb3/tqc-LunarLanderContinuous-v2 | null | [
"stable-baselines3",
"LunarLanderContinuous-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T18:03:19+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing LunarLanderContinuous-v2
This is a trained model of a TQC 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... | [
"# TQC Agent playing LunarLanderContinuous-v2\nThis is a trained model of a TQC 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",
"# TQC Agent playing LunarLanderContinuous-v2\nThis is a trained model of a TQC agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **BipedalWalker-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | sb3/tqc-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T18:20:35+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing BipedalWalker-v3
This is a trained model of a TQC 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 (... | [
"# TQC Agent playing BipedalWalker-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing BipedalWalker-v3\nThis is a trained model of a TQC agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fra... |
null | keras |
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': ... | {"library_name": "keras", "tags": ["mol_gen"]} | IshanKumar/molecular_generation | null | [
"keras",
"tensorboard",
"mol_gen",
"region:us"
] | null | 2022-06-02T18:30:33+00:00 | [] | [] | TAGS
#keras #tensorboard #mol_gen #region-us
| Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following h... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 0.0005, 'decay': 0.0, 'beta\\_1': 0.9, 'beta\\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}\n* training\\_precision: float32\n\n\nTraining Metrics\n----------------\n\n... | [
"TAGS\n#keras #tensorboard #mol_gen #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 0.0005, 'decay': 0.0, 'beta\\_1': 0.9, 'beta\\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}\n* training\\_precisio... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **PandaPush-v1**
This is a trained model of a **TQC** agent playing **PandaPush-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": ["PandaPush-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaPush-v1", "type": "PandaPush-... | sb3/tqc-PandaPush-v1 | null | [
"stable-baselines3",
"PandaPush-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"arxiv:2106.13687",
"model-index",
"region:us"
] | null | 2022-06-02T18:37:51+00:00 | [
"2106.13687"
] | [] | TAGS
#stable-baselines3 #PandaPush-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us
|
# TQC Agent playing PandaPush-v1
This is a trained model of a TQC agent playing PandaPush-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... | [
"# TQC Agent playing PandaPush-v1\nThis is a trained model of a TQC agent playing PandaPush-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 #PandaPush-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us \n",
"# TQC Agent playing PandaPush-v1\nThis is a trained model of a TQC agent playing PandaPush-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a traini... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **BipedalWalkerHardcore-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalkerHardcore-... | sb3/tqc-BipedalWalkerHardcore-v3 | null | [
"stable-baselines3",
"BipedalWalkerHardcore-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T18:39:41+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalkerHardcore-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing BipedalWalkerHardcore-v3
This is a trained model of a TQC 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... | [
"# TQC Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing BipedalWalkerHardcore-v3\nThis is a trained model of a TQC agent playing BipedalWalkerHardcore-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe ... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **Walker2DBulletEnv-v0**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2DBulletEnv-v0", "ty... | sb3/tqc-Walker2DBulletEnv-v0 | null | [
"stable-baselines3",
"Walker2DBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T18:57:09+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing Walker2DBulletEnv-v0
This is a trained model of a TQC 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.
##... | [
"# TQC Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a TQC 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",
"# TQC Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a TQC agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **PandaReach-v1**
This is a trained model of a **TQC** agent playing **PandaReach-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": ["PandaReach-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReach-v1", "type": "PandaRea... | sb3/tqc-PandaReach-v1 | null | [
"stable-baselines3",
"PandaReach-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"arxiv:2106.13687",
"model-index",
"region:us"
] | null | 2022-06-02T18:58:18+00:00 | [
"2106.13687"
] | [] | TAGS
#stable-baselines3 #PandaReach-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us
|
# TQC Agent playing PandaReach-v1
This is a trained model of a TQC agent playing PandaReach-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... | [
"# TQC Agent playing PandaReach-v1\nThis is a trained model of a TQC agent playing PandaReach-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 #PandaReach-v1 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us \n",
"# TQC Agent playing PandaReach-v1\nThis is a trained model of a TQC agent playing PandaReach-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a tra... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **MountainCarContinuous-v0**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCarContinuous-... | sb3/tqc-MountainCarContinuous-v0 | null | [
"stable-baselines3",
"MountainCarContinuous-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T18:59:59+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing MountainCarContinuous-v0
This is a trained model of a TQC 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... | [
"# TQC Agent playing MountainCarContinuous-v0\nThis is a trained model of a TQC 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",
"# TQC Agent playing MountainCarContinuous-v0\nThis is a trained model of a TQC agent playing MountainCarContinuous-v0\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... | SimulSt/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 | 2022-06-02T19:04:01+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: 0.2202
* Accuracy: 0.925
* F1: 0.9250
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... |
feature-extraction | transformers |
# Patent CPC Predictor
This is a fine-tuned version of microsoft/deberta-v3-small for predicting Patent CPC codes.
# Dataset
Dataset consists of titles and abstracts sampled from granted patent applications:
https://www.kaggle.com/datasets/grimmace/sampled-patent-titles
# Results
| Category | Accuracy |
| --- | -... | {"language": "en", "license": "mit", "tags": ["patent", "deberta"]} | bradgrimm/patent-cpc-predictor | null | [
"transformers",
"pytorch",
"safetensors",
"deberta-v2",
"feature-extraction",
"patent",
"deberta",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T19:06:22+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #deberta-v2 #feature-extraction #patent #deberta #en #license-mit #endpoints_compatible #region-us
| Patent CPC Predictor
====================
This is a fine-tuned version of microsoft/deberta-v3-small for predicting Patent CPC codes.
Dataset
=======
Dataset consists of titles and abstracts sampled from granted patent applications:
URL
Results
=======
| [] | [
"TAGS\n#transformers #pytorch #safetensors #deberta-v2 #feature-extraction #patent #deberta #en #license-mit #endpoints_compatible #region-us \n"
] |
text2text-generation | transformers |
This model is a fine-tune checkpoint of [T5-large](https://huggingface.co/t5-large), fine-tuned on the [Wiki Neutrality Corpus (WNC)](https://github.com/rpryzant/neutralizing-bias), a labeled dataset composed of 180,000 biased and neutralized sentence pairs that are generated from Wikipedia edits tagged for βneutral p... | {"language": ["en"], "license": "apache-2.0", "datasets": ["WNC"], "metrics": ["accuracy"]} | erickfm/t5-large-finetuned-bias | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:WNC",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T19:07:14+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #t5 #text2text-generation #en #dataset-WNC #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
This model is a fine-tune checkpoint of T5-large, fine-tuned on the Wiki Neutrality Corpus (WNC), a labeled dataset composed of 180,000 biased and neutralized sentence pairs that are generated from Wikipedia edits tagged for βneutral point of viewβ. This model reaches an accuracy of [?] on a dev split of the WNC.
For... | [] | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #en #dataset-WNC #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **Ant-v3**
This is a trained model of a **TQC** 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": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Ant-v3", "type": "Ant-v3"}, "metrics": [... | sb3/tqc-Ant-v3 | null | [
"stable-baselines3",
"Ant-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:17:17+00:00 | [] | [] | TAGS
#stable-baselines3 #Ant-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing Ant-v3
This is a trained model of a TQC 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... | [
"# TQC Agent playing Ant-v3\nThis is a trained model of a TQC 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",
"# TQC Agent playing Ant-v3\nThis is a trained model of a TQC 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 |
# **DDPG** Agent playing **AntBulletEnv-v0**
This is a trained model of a **DDPG** 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 Baselines... | {"library_name": "stable-baselines3", "tags": ["AntBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "AntBulletEnv-v0", "type": "Ant... | sb3/ddpg-AntBulletEnv-v0 | null | [
"stable-baselines3",
"AntBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:18:11+00:00 | [] | [] | TAGS
#stable-baselines3 #AntBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing AntBulletEnv-v0
This is a trained model of a DDPG 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 (... | [
"# DDPG Agent playing AntBulletEnv-v0\nThis is a trained model of a DDPG 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",
"# DDPG Agent playing AntBulletEnv-v0\nThis is a trained model of a DDPG agent playing AntBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fram... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **ReacherBulletEnv-v0**
This is a trained model of a **DDPG** 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 B... | {"library_name": "stable-baselines3", "tags": ["ReacherBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "ReacherBulletEnv-v0", "typ... | sb3/ddpg-ReacherBulletEnv-v0 | null | [
"stable-baselines3",
"ReacherBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:19:14+00:00 | [] | [] | TAGS
#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing ReacherBulletEnv-v0
This is a trained model of a DDPG 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.
##... | [
"# DDPG Agent playing ReacherBulletEnv-v0\nThis is a trained model of a DDPG 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 in... | [
"TAGS\n#stable-baselines3 #ReacherBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing ReacherBulletEnv-v0\nThis is a trained model of a DDPG agent playing ReacherBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a t... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **HopperBulletEnv-v0**
This is a trained model of a **DDPG** 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 Bas... | {"library_name": "stable-baselines3", "tags": ["HopperBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HopperBulletEnv-v0", "type"... | sb3/ddpg-HopperBulletEnv-v0 | null | [
"stable-baselines3",
"HopperBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:20:17+00:00 | [] | [] | TAGS
#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing HopperBulletEnv-v0
This is a trained model of a DDPG 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.
## U... | [
"# DDPG Agent playing HopperBulletEnv-v0\nThis is a trained model of a DDPG 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 incl... | [
"TAGS\n#stable-baselines3 #HopperBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing HopperBulletEnv-v0\nThis is a trained model of a DDPG agent playing HopperBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a trai... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **HalfCheetahBulletEnv-v0**
This is a trained model of a **DDPG** 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 ... | {"library_name": "stable-baselines3", "tags": ["HalfCheetahBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "HalfCheetahBulletEnv-v... | sb3/ddpg-HalfCheetahBulletEnv-v0 | null | [
"stable-baselines3",
"HalfCheetahBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:21:10+00:00 | [] | [] | TAGS
#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing HalfCheetahBulletEnv-v0
This is a trained model of a DDPG 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 inclu... | [
"# DDPG Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a DDPG 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 a... | [
"TAGS\n#stable-baselines3 #HalfCheetahBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing HalfCheetahBulletEnv-v0\nThis is a trained model of a DDPG agent playing HalfCheetahBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe R... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **Pendulum-v1**
This is a trained model of a **DDPG** 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
reinfo... | {"library_name": "stable-baselines3", "tags": ["Pendulum-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pendulum-v1", "type": "Pendulum-v1... | sb3/ddpg-Pendulum-v1 | null | [
"stable-baselines3",
"Pendulum-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:22:09+00:00 | [] | [] | TAGS
#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing Pendulum-v1
This is a trained model of a DDPG 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... | [
"# DDPG Agent playing Pendulum-v1\nThis is a trained model of a DDPG 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.",
"## ... | [
"TAGS\n#stable-baselines3 #Pendulum-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing Pendulum-v1\nThis is a trained model of a DDPG agent playing Pendulum-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for St... |
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
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"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... | ponci/ppo-lunar-ponci-test | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:32:15+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\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **LunarLanderContinuous-v2**
This is a trained model of a **DDPG** 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 fo... | {"library_name": "stable-baselines3", "tags": ["LunarLanderContinuous-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLanderContinuous... | sb3/ddpg-LunarLanderContinuous-v2 | null | [
"stable-baselines3",
"LunarLanderContinuous-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:39:19+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing LunarLanderContinuous-v2
This is a trained model of a DDPG 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 inc... | [
"# DDPG Agent playing LunarLanderContinuous-v2\nThis is a trained model of a DDPG 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... | [
"TAGS\n#stable-baselines3 #LunarLanderContinuous-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing LunarLanderContinuous-v2\nThis is a trained model of a DDPG agent playing LunarLanderContinuous-v2\nusing the stable-baselines3 library\nand the RL Zoo.\n\nTh... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **BipedalWalker-v3**
This is a trained model of a **DDPG** 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 Baselin... | {"library_name": "stable-baselines3", "tags": ["BipedalWalker-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "B... | sb3/ddpg-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:42:17+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing BipedalWalker-v3
This is a trained model of a DDPG 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... | [
"# DDPG Agent playing BipedalWalker-v3\nThis is a trained model of a DDPG 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",
"# DDPG Agent playing BipedalWalker-v3\nThis is a trained model of a DDPG agent playing BipedalWalker-v3\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training f... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **Walker2DBulletEnv-v0**
This is a trained model of a **DDPG** 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... | {"library_name": "stable-baselines3", "tags": ["Walker2DBulletEnv-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Walker2DBulletEnv-v0", "t... | sb3/ddpg-Walker2DBulletEnv-v0 | null | [
"stable-baselines3",
"Walker2DBulletEnv-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:43:12+00:00 | [] | [] | TAGS
#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing Walker2DBulletEnv-v0
This is a trained model of a DDPG 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.
... | [
"# DDPG Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a DDPG 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 ... | [
"TAGS\n#stable-baselines3 #Walker2DBulletEnv-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing Walker2DBulletEnv-v0\nThis is a trained model of a DDPG agent playing Walker2DBulletEnv-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is ... |
reinforcement-learning | stable-baselines3 |
# **DDPG** Agent playing **MountainCarContinuous-v0**
This is a trained model of a **DDPG** 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 fo... | {"library_name": "stable-baselines3", "tags": ["MountainCarContinuous-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DDPG", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "MountainCarContinuous... | sb3/ddpg-MountainCarContinuous-v0 | null | [
"stable-baselines3",
"MountainCarContinuous-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:44:09+00:00 | [] | [] | TAGS
#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DDPG Agent playing MountainCarContinuous-v0
This is a trained model of a DDPG 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 inc... | [
"# DDPG Agent playing MountainCarContinuous-v0\nThis is a trained model of a DDPG 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... | [
"TAGS\n#stable-baselines3 #MountainCarContinuous-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DDPG Agent playing MountainCarContinuous-v0\nThis is a trained model of a DDPG agent playing MountainCarContinuous-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nTh... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **FetchReach-v1**
This is a trained model of a **TQC** agent playing **FetchReach-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": ["FetchReach-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FetchReach-v1", "type": "FetchRea... | sb3/tqc-FetchReach-v1 | null | [
"stable-baselines3",
"FetchReach-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:54:49+00:00 | [] | [] | TAGS
#stable-baselines3 #FetchReach-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing FetchReach-v1
This is a trained model of a TQC agent playing FetchReach-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... | [
"# TQC Agent playing FetchReach-v1\nThis is a trained model of a TQC agent playing FetchReach-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 #FetchReach-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TQC Agent playing FetchReach-v1\nThis is a trained model of a TQC agent playing FetchReach-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework fo... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **FetchPush-v1**
This is a trained model of a **TQC** agent playing **FetchPush-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": ["FetchPush-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FetchPush-v1", "type": "FetchPush-... | sb3/tqc-FetchPush-v1 | null | [
"stable-baselines3",
"FetchPush-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:55:29+00:00 | [] | [] | TAGS
#stable-baselines3 #FetchPush-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing FetchPush-v1
This is a trained model of a TQC agent playing FetchPush-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... | [
"# TQC Agent playing FetchPush-v1\nThis is a trained model of a TQC agent playing FetchPush-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 #FetchPush-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TQC Agent playing FetchPush-v1\nThis is a trained model of a TQC agent playing FetchPush-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for S... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **FetchSlide-v1**
This is a trained model of a **TQC** agent playing **FetchSlide-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": ["FetchSlide-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FetchSlide-v1", "type": "FetchSli... | sb3/tqc-FetchSlide-v1 | null | [
"stable-baselines3",
"FetchSlide-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:56:18+00:00 | [] | [] | TAGS
#stable-baselines3 #FetchSlide-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing FetchSlide-v1
This is a trained model of a TQC agent playing FetchSlide-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... | [
"# TQC Agent playing FetchSlide-v1\nThis is a trained model of a TQC agent playing FetchSlide-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 #FetchSlide-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TQC Agent playing FetchSlide-v1\nThis is a trained model of a TQC agent playing FetchSlide-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework fo... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **parking-v0**
This is a trained model of a **TQC** agent playing **parking-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
reinforcem... | {"library_name": "stable-baselines3", "tags": ["parking-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "parking-v0", "type": "parking-v0"}, ... | sb3/tqc-parking-v0 | null | [
"stable-baselines3",
"parking-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:57:08+00:00 | [] | [] | TAGS
#stable-baselines3 #parking-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing parking-v0
This is a trained model of a TQC agent playing parking-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 (with SB3 RL ... | [
"# TQC Agent playing parking-v0\nThis is a trained model of a TQC agent playing parking-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.",
"## Usag... | [
"TAGS\n#stable-baselines3 #parking-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TQC Agent playing parking-v0\nThis is a trained model of a TQC agent playing parking-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable ... |
reinforcement-learning | stable-baselines3 |
# **TQC** Agent playing **FetchPickAndPlace-v1**
This is a trained model of a **TQC** agent playing **FetchPickAndPlace-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 B... | {"library_name": "stable-baselines3", "tags": ["FetchPickAndPlace-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "TQC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FetchPickAndPlace-v1", "ty... | sb3/tqc-FetchPickAndPlace-v1 | null | [
"stable-baselines3",
"FetchPickAndPlace-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-06-02T19:58:19+00:00 | [] | [] | TAGS
#stable-baselines3 #FetchPickAndPlace-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# TQC Agent playing FetchPickAndPlace-v1
This is a trained model of a TQC agent playing FetchPickAndPlace-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.
##... | [
"# TQC Agent playing FetchPickAndPlace-v1\nThis is a trained model of a TQC agent playing FetchPickAndPlace-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 in... | [
"TAGS\n#stable-baselines3 #FetchPickAndPlace-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TQC Agent playing FetchPickAndPlace-v1\nThis is a trained model of a TQC agent playing FetchPickAndPlace-v1\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
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-colab53
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-timit-demo-colab53", "results": []}]} | Mudassar/wav2vec2-base-timit-demo-colab53 | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T20:09:11+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-colab53
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training ... | [
"# wav2vec2-base-timit-demo-colab53\n\nThis model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Trainin... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"# wav2vec2-base-timit-demo-colab53\n\nThis model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.",
"## Model description\n\... |
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. -->
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["rotten_tomatoes_movie_review"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "finetuning-sentiment-model-3000-samples", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "rotten_... | symons/finetuning-sentiment-model-3000-samples | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:rotten_tomatoes_movie_review",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T20:15:34+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-rotten_tomatoes_movie_review #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of distilbert-base-uncased on the rotten_tomatoes_movie_review dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8692
- Accuracy: 0.8433
- F1: 0.8407
## Model description
More information needed
## Intended use... | [
"# finetuning-sentiment-model-3000-samples\n\nThis model is a fine-tuned version of distilbert-base-uncased on the rotten_tomatoes_movie_review dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.8692\n- Accuracy: 0.8433\n- F1: 0.8407",
"## Model description\n\nMore information needed",
... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-rotten_tomatoes_movie_review #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# finetuning-sentiment-model-3000-samples\n\nThis model is a fine-tuned version of... |
null | null | git lfs install
git clone https://huggingface.co/etmckinley/BERFALTER
# if you want to clone without large files β just their pointers
# prepend your git clone with the following env var:
GIT_LFS_SKIP_SMUDGE=1 | {} | benwri/GaryOut | null | [
"region:us"
] | null | 2022-06-02T20:18:55+00:00 | [] | [] | TAGS
#region-us
| git lfs install
git clone URL
# if you want to clone without large files β just their pointers
# prepend your git clone with the following env var:
GIT_LFS_SKIP_SMUDGE=1 | [
"# if you want to clone without large files β just their pointers",
"# prepend your git clone with the following env var:\nGIT_LFS_SKIP_SMUDGE=1"
] | [
"TAGS\n#region-us \n",
"# if you want to clone without large files β just their pointers",
"# prepend your git clone with the following env var:\nGIT_LFS_SKIP_SMUDGE=1"
] |
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/914206875419332608/26FrQ... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/mrikasper/1654206041092/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/mrikasper | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T20:39:59+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Lars Kasper
@mrikasper
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-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": []}]} | sanamoin/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 | 2022-06-02T20:42:05+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.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Trai... | [
"# wav2vec2-base-timit-demo-google-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Tr... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"# wav2vec2-base-timit-demo-google-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.",
"## Model descripti... |
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. -->
# TC01_Trabalho01
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "TC01_Trabalho01", "results": []}]} | Lorenzo1708/TC01_Trabalho01 | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T20:42:50+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# TC01_Trabalho01
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2714
- Accuracy: 0.8979
- F1: 0.8972
## Model description
More information needed
## Intended uses & limitations
More information needed
## T... | [
"# TC01_Trabalho01\n\nThis model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.2714\n- Accuracy: 0.8979\n- F1: 0.8972",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore info... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# TC01_Trabalho01\n\nThis model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.\nIt achieves the following ... |
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. -->
# bert-base-cased-finetuned-squad
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "bert-base-cased-finetuned-squad", "results": []}]} | victorlee071200/bert-base-cased-finetuned-squad | null | [
"transformers",
"pytorch",
"bert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T20:56:46+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
| bert-base-cased-finetuned-squad
===============================
This model is a fine-tuned version of bert-base-cased on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0835
Model description
-----------------
More information needed
Intended uses & limitations
----------... | [
"### 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: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #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: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_b... |
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. -->
# distilbert-base-cased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/disti... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "distilbert-base-cased-finetuned-squad", "results": []}]} | victorlee071200/distilbert-base-cased-finetuned-squad | null | [
"transformers",
"pytorch",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T21:08:20+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
| distilbert-base-cased-finetuned-squad
=====================================
This model is a fine-tuned version of distilbert-base-cased on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1755
Model description
-----------------
More information needed
Intended uses & limi... | [
"### 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: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #distilbert #question-answering #generated_from_trainer #dataset-squad #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: 2e-05\n* train\\_batch\\_size: 16\n* ev... |
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/1211158441504456704/dCNS... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/the_dealersh1p/1668510925052/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/the_dealersh1p | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T21:24:34+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
γ γγdanγγ γ
@the\_dealersh1p
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"
] |
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/1239803946643927041/AHuD... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/marazack26/1654210546142/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/marazack26 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T21:54:27+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Mohammed Abd Al-Razack / Ω
ΨΩ
Ψ― ΨΉΨ¨Ψ― Ψ§ΩΨ±Ψ²Ψ§Ω
@marazack26
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 repo... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
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/1274320386881183747/NJTJ... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/joanacspinto/1654210973627/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/joanacspinto | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T22:02:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Dr Joana Pinto
@joanacspinto
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"
] |
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/1443195119218343937/dNb4... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/chewschaper/1654211222982/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/chewschaper | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T22:06:40+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Benjamin Schaper
@chewschaper
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"
] |
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. -->
# distilroberta-base-finetuned-squad
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilrober... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "distilroberta-base-finetuned-squad", "results": []}]} | victorlee071200/distilroberta-base-finetuned-squad | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T22:21:57+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
| distilroberta-base-finetuned-squad
==================================
This model is a fine-tuned version of distilroberta-base on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0014
Model description
-----------------
More information needed
Intended uses & limitations
-... | [
"### 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: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #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: 2e-05\n* train\\_batch\\_size: 16\n* eval\... |
null | 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. -->
# xtreme_s_xlsr_t5lephone-small_minds14.en-all
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggin... | {"language": ["all"], "license": "apache-2.0", "tags": ["minds14", "google/xtreme_s", "generated_from_trainer"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "xtreme_s_xlsr_t5lephone-small_minds14.en-all", "results": []}]} | Splend1dchan/xtreme_s_xlsr_t5lephone-small_minds14.en-all | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"minds14",
"google/xtreme_s",
"generated_from_trainer",
"all",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-02T22:38:15+00:00 | [] | [
"all"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #minds14 #google/xtreme_s #generated_from_trainer #all #license-apache-2.0 #endpoints_compatible #region-us
| xtreme\_s\_xlsr\_t5lephone-small\_minds14.en-all
================================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME\_S - MINDS14.ALL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5979
* F1: 0.8918
* Accuracy: 0.8921
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* distributed\\_type: multi-GPU\n* num\\_devices: 2\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 32\n... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #minds14 #google/xtreme_s #generated_from_trainer #all #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* train\\_batch\\_size: ... |
text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# mt5-small-summarization
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknow... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "mt5-small-summarization", "results": []}]} | hananajiyya/mt5-small-summarization | null | [
"transformers",
"tf",
"mt5",
"text2text-generation",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-02T23:27:50+00:00 | [] | [] | TAGS
#transformers #tf #mt5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| mt5-small-summarization
=======================
This model is a fine-tuned version of google/mt5-small on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 2.9665
* Validation Loss: 2.4241
* Train Rouge1: 23.5645
* Train Rouge2: 8.2413
* Train Rougel: 19.7515
* Train Rougels... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': 2e-05, 'decay': 0.0, 'beta\\_1': 0.9, 'beta\\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight\\_decay\\_rate': 0.01}\n* training\\_precision: float32",
... | [
"TAGS\n#transformers #tf #mt5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam... |
text2text-generation | transformers |
In this example model, I want to test how to summarize a short text due a very very small corpus of data used to train it. The data contains two columns: Text and Summary. This model was created in python through Google Colab interface, with the hugging face librarys for this task.
Diego Villada | {"license": "cc-by-4.0"} | DVillada/T5_fine_tunning_NLP_test | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-03T01:14:18+00:00 | [] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
In this example model, I want to test how to summarize a short text due a very very small corpus of data used to train it. The data contains two columns: Text and Summary. This model was created in python through Google Colab interface, with the hugging face librarys for this task.
Diego Villada | [] | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
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="kalmufti/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional att... | {"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": ... | kalmufti/q-FrozenLake-v1-4x4-noSlippery | null | [
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] | null | 2022-06-03T01:26:55+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"
] |
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. -->
# wav2vec2-23
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-23", "results": []}]} | chrisvinsen/wav2vec2-23 | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-03T01:59:14+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-23
===========
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: 3.1230
* Wer: 1.0
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\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: 0.0003\n* train\\_batch\\_size: 3... |
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-hindi-bhoj-3
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-hindi-bhoj-3", "results": []}]} | sriiikar/wav2vec2-hindi-bhoj-3 | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-06-03T03:23:42+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-hindi-bhoj-3
=====================
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 5.7033
* Wer: 1.1477
Model description
-----------------
More information needed
Intended uses & limitations
-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"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: 1... |
question-answering | transformers | # Model
---
## [KLUE MRC λν](https://github.com/boostcampaitech3/level2-mrc-level2-nlp-09)μμ μ¬μ©ν Reader SOTAλͺ¨λΈμ μ¬μ©νμ¬ νμΈνλμ μ§ννμ΅λλ€.
- λ°μ΄ν°μ
: νκΉ
μ΄ν ꡬμΆν λ°μ΄ν°μ
μμ μ μ²λ¦¬ λ° Augmentation μ μ©
- [Huggingface : MRC Reader SOTA λͺ¨λΈ](https://huggingface.co/Nonegom/roberta_finetune_twice)
- [Github Issue : MRC Redaer SOTA λͺ¨λΈ μ€λͺ
](https://... | {} | wogkr810/mnm | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"endpoints_compatible",
"region:us"
] | null | 2022-06-03T03:33:50+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #endpoints_compatible #region-us
| # Model
---
## KLUE MRC λνμμ μ¬μ©ν Reader SOTAλͺ¨λΈμ μ¬μ©νμ¬ νμΈνλμ μ§ννμ΅λλ€.
- λ°μ΄ν°μ
: νκΉ
μ΄ν ꡬμΆν λ°μ΄ν°μ
μμ μ μ²λ¦¬ λ° Augmentation μ μ©
- Huggingface : MRC Reader SOTA λͺ¨λΈ
- Github Issue : MRC Redaer SOTA λͺ¨λΈ μ€λͺ
| [
"# Model\n---",
"## KLUE MRC λνμμ μ¬μ©ν Reader SOTAλͺ¨λΈμ μ¬μ©νμ¬ νμΈνλμ μ§ννμ΅λλ€.\n- λ°μ΄ν°μ
: νκΉ
μ΄ν ꡬμΆν λ°μ΄ν°μ
μμ μ μ²λ¦¬ λ° Augmentation μ μ©\n- Huggingface : MRC Reader SOTA λͺ¨λΈ\n- Github Issue : MRC Redaer SOTA λͺ¨λΈ μ€λͺ
"
] | [
"TAGS\n#transformers #pytorch #roberta #question-answering #endpoints_compatible #region-us \n",
"# Model\n---",
"## KLUE MRC λνμμ μ¬μ©ν Reader SOTAλͺ¨λΈμ μ¬μ©νμ¬ νμΈνλμ μ§ννμ΅λλ€.\n- λ°μ΄ν°μ
: νκΉ
μ΄ν ꡬμΆν λ°μ΄ν°μ
μμ μ μ²λ¦¬ λ° Augmentation μ μ©\n- Huggingface : MRC Reader SOTA λͺ¨λΈ\n- Github Issue : MRC Redaer SOTA λͺ¨λΈ μ€λͺ
"
] |
text-generation | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# opt-1.3b
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## Mode... | {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "opt-1.3b", "results": []}]} | ArthurZ/opt-1.3b | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-06-03T04:20:01+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# opt-1.3b
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
##... | [
"# opt-1.3b\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:",
"## 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 #tf #jax #opt #text-generation #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# opt-1.3b\n\nThis model was trained from scratch on an unknown dataset.\nIt achieves the following results on the evaluation set:",
... |
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