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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. -->
# roberta-large-initialization-seed-2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) ... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-initialization-seed-2", "results": []}]} | anas-awadalla/roberta-large-initialization-seed-2 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T15:48:32+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-initialization-seed-2
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyper... | [
"# roberta-large-initialization-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training pro... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-initialization-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information nee... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **BipedalWalker-v3**
This is a trained model of a **PPO** agent playing **BipedalWalker-v3** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["BipedalWalker-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | DBusAI/PPO-BipedalWalker-v3-v2_1_same_submit | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T15:54:12+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing BipedalWalker-v3
This is a trained model of a PPO agent playing BipedalWalker-v3 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing BipedalWalker-v3\n This is a trained model of a PPO agent playing BipedalWalker-v3 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing BipedalWalker-v3\n This is a trained model of a PPO agent playing BipedalWalker-v3 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TO... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | JLD/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T15:57:12+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-generation | 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. -->
# gpt2-example
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
## Model descript... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-example", "results": []}]} | Dizzykong/gpt2-example | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-13T17:00:30+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# gpt2-example
This model is a fine-tuned version of gpt2 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyper... | [
"# gpt2-example\n\nThis model is a fine-tuned version of gpt2 on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperp... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# gpt2-example\n\nThis model is a fine-tuned version of gpt2 on an unknown dataset.",
"## Model description\n\nMore infor... |
fill-mask | 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. -->
# en-TAPT-MLM-MiniLM
This model is a fine-tuned version of [subhasisj/MiniLMv2-qa-encoder](https://huggingface.co/subhasisj/MiniLM... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "en-TAPT-MLM-MiniLM", "results": []}]} | subhasisj/en-TAPT-MLM-MiniLM | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T17:46:52+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
|
# en-TAPT-MLM-MiniLM
This model is a fine-tuned version of subhasisj/MiniLMv2-qa-encoder on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyper... | [
"# en-TAPT-MLM-MiniLM\n\nThis model is a fine-tuned version of subhasisj/MiniLMv2-qa-encoder on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training pro... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us \n",
"# en-TAPT-MLM-MiniLM\n\nThis model is a fine-tuned version of subhasisj/MiniLMv2-qa-encoder on an unknown dataset.",
"## Model description\n\nMore information needed",... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nikiandr/PPO-LunarLanderv2-5e5t | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T18:00:10+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
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. -->
# roberta-large-initialization-seed-4
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) ... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-initialization-seed-4", "results": []}]} | anas-awadalla/roberta-large-initialization-seed-4 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T18:00:31+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-initialization-seed-4
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyper... | [
"# roberta-large-initialization-seed-4\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training pro... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-initialization-seed-4\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information nee... |
null | null | For training purpose only! | {} | Ranit/my_model | null | [
"region:us"
] | null | 2022-05-13T18:32:08+00:00 | [] | [] | TAGS
#region-us
| For training purpose only! | [] | [
"TAGS\n#region-us \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. -->
# TAPE-finetuned-viralProteins
This model was trained from scratch on the None dataset.
It achieves the following results on the e... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "TAPE-finetuned-viralProteins", "results": []}]} | nepp1d0/TAPE-finetuned-viralProteins | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T18:33:59+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
| TAPE-finetuned-viralProteins
============================
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9033
* Accuracy: 0.87
* F1: 0.8555
* Precision: 0.8475
* Recall: 0.87
Model description
-----------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 1\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* num\\_epochs: 10\n* mixed\\_preci... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 1\n* eval\\_b... |
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).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nikiandr/DQN-LunarLanderv2-5e5t | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T18:35:20+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.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# DQN Agent playing LunarLander-v2\n This is a trained model of a DQN agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing LunarLander-v2\n This is a trained model of a DQN agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
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. -->
# en-finetuned-squad-qa-minilmv2-32
This model is a fine-tuned version of [subhasisj/en-TAPT-MLM-MiniLM](https://huggingface.co/su... | {"tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "en-finetuned-squad-qa-minilmv2-32", "results": []}]} | subhasisj/en-finetuned-squad-qa-minilmv2-32 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T18:47:17+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #dataset-squad #endpoints_compatible #region-us
| en-finetuned-squad-qa-minilmv2-32
=================================
This model is a fine-tuned version of subhasisj/en-TAPT-MLM-MiniLM on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1955
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 256\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #dataset-squad #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_... |
reinforcement-learning | stable-baselines3 |
# **RecurrentPPO** Agent playing **CarRacing-v0**
This is a trained model of a **RecurrentPPO** agent playing **CarRacing-v0** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
Using recurrent PPO implementation fro... | {"library_name": "stable-baselines3", "tags": ["CarRacing-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "RecurrentPPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CarRacing-v0", "type": "C... | araffin/RecurrentPPO-CarRacing-v0 | null | [
"stable-baselines3",
"CarRacing-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T19:24:51+00:00 | [] | [] | TAGS
#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# RecurrentPPO Agent playing CarRacing-v0
This is a trained model of a RecurrentPPO agent playing CarRacing-v0 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
Using recurrent PPO implementation from SB3 contrib: URL
| [
"# RecurrentPPO Agent playing CarRacing-v0\n This is a trained model of a RecurrentPPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code\n \n Using recurrent PPO implementation from SB3 contrib: URL"
] | [
"TAGS\n#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# RecurrentPPO Agent playing CarRacing-v0\n This is a trained model of a RecurrentPPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)... |
multiple-choice | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-race
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the N... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "bert-finetuned-race", "results": []}]} | pidanr/bert-finetuned-race | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"multiple-choice",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T19:26:25+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| bert-finetuned-race
===================
This model is a fine-tuned version of bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.3863
* Accuracy: 0.2982
Model description
-----------------
More information needed
Intended uses & limitations
--------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #multiple-choice #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: 5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\... |
text-generation | 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. -->
# codeparrot-ds
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the f... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "codeparrot-ds", "results": []}]} | SebastianS/codeparrot-ds | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-13T19:46:53+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| codeparrot-ds
=============
This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.4905
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 256\n* optimizer: Adam with betas=(0.9,0.999) and epsil... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n... |
text2text-generation | 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. -->
# meeting-summary
This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["samsum"], "model-index": [{"name": "meeting-summary", "results": []}]} | tanviraumi/meeting-summary | null | [
"transformers",
"pytorch",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"dataset:samsum",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T20:12:46+00:00 | [] | [] | TAGS
#transformers #pytorch #safetensors #bart #text2text-generation #generated_from_trainer #dataset-samsum #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# meeting-summary
This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamete... | [
"# meeting-summary\n\nThis model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",... | [
"TAGS\n#transformers #pytorch #safetensors #bart #text2text-generation #generated_from_trainer #dataset-samsum #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# meeting-summary\n\nThis model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset.",
"## Model descript... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | Kommunarus/ppo_rl-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T20:23:58+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-expense-ner
This model is a fine-tuned version of [renjithks/distilbert-cord-ner](https://huggingface.co/renjithks/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilbert-expense-ner", "results": []}]} | renjithks/distilbert-expense-ner | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-13T20:36:41+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| distilbert-expense-ner
======================
This model is a fine-tuned version of renjithks/distilbert-cord-ner on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2930
* Precision: 0.5096
* Recall: 0.4852
* F1: 0.4971
* Accuracy: 0.9275
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Trainin... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\... |
image-classification | transformers |
# computer-stuff
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
Report any issues with the demo at the [github repo](https://github.com/nateraw/huggi... | {"tags": ["image-classification", "pytorch", "huggingpics"], "metrics": ["accuracy"]} | iyzg/computer-stuff | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T20:55:38+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# computer-stuff
Autogenerated by HuggingPics️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
## Example Images
#### computer mouse
!computer mouse
#### desktop
!desktop
#### keyboard
!keyboard
#### laptop
!laptop
#... | [
"# computer-stuff\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.",
"## Example Images",
"#### computer mouse\n\n!computer mouse",
"#### desktop\n\n!desktop",
"#### keyboard\n\n!ke... | [
"TAGS\n#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# computer-stuff\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issue... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **CarRacing-v0**
This is a trained model of a **PPO** agent playing **CarRacing-v0** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["CarRacing-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CarRacing-v0", "type": "CarRacing-... | vukpetar/ppo-CarRacing-v0-v1 | null | [
"stable-baselines3",
"CarRacing-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T21:03:40+00:00 | [] | [] | TAGS
#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing CarRacing-v0
This is a trained model of a PPO agent playing CarRacing-v0 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing CarRacing-v0\n This is a trained model of a PPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing CarRacing-v0\n This is a trained model of a PPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your... |
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. -->
# deepavlov-test-bert-2
This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rub... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "deepavlov-test-bert-2", "results": []}]} | ruselkomp/deepavlov-framebank-10size | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T21:08:47+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #endpoints_compatible #region-us
| deepavlov-test-bert-2
=====================
This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1607
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: 10\n* eval\\_batch\\_size: 10\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 #bert #question-answering #generated_from_trainer #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: 10\n* eval\\_batch\\_size: 10\n* see... |
text-generation | transformers |
# Corroded MercBot DialoGPT Model | {"tags": ["conversational"]} | SNCannon/DialoGPT-medium-merc | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-13T21:34:40+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Corroded MercBot DialoGPT Model | [
"# Corroded MercBot DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Corroded MercBot DialoGPT Model"
] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | bstad/ppo-LunarLander-v2-n_envs-32 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T21:36:52+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
fill-mask | 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. -->
# mateotyz/tf-xml-r-base-ape
This model is a fine-tuned version of [jplu/tf-xlm-roberta-base](https://huggingface.co/jplu/tf-xlm-roberta... | {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "mateotyz/tf-xml-r-base-ape", "results": []}]} | mateotyz/tf-xml-r-base-ape-wwm | null | [
"transformers",
"tf",
"tensorboard",
"xlm-roberta",
"fill-mask",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-13T21:44:57+00:00 | [] | [] | TAGS
#transformers #tf #tensorboard #xlm-roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us
| mateotyz/tf-xml-r-base-ape
==========================
This model is a fine-tuned version of jplu/tf-xlm-roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.3189
* Validation Loss: 0.2796
* Epoch: 2
Model description
-----------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'WarmUp', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_schedule\\_fn': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_le... | [
"TAGS\n#transformers #tf #tensorboard #xlm-roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'cl... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | arampacha/LunarLander-v2-ppo-3 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T21:49:28+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **RPPO** Agent playing **CarRacing-v0**
This is a trained model of a **RPPO** agent playing **CarRacing-v0** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["CarRacing-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "RPPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CarRacing-v0", "type": "CarRacing... | DBusAI/RPPO-CarRacing-v0 | null | [
"stable-baselines3",
"CarRacing-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T21:52:43+00:00 | [] | [] | TAGS
#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# RPPO Agent playing CarRacing-v0
This is a trained model of a RPPO agent playing CarRacing-v0 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# RPPO Agent playing CarRacing-v0\n This is a trained model of a RPPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# RPPO Agent playing CarRacing-v0\n This is a trained model of a RPPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add yo... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | grunty/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T21:58:57+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | kvaky/course-lunar-lander | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T22:10:45+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | bstad/ppo-LunarLander-v2-n_envs-32-steps-2e6 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-13T22:30:28+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
null | null |
[click me](https://www.youtube.com/watch?v=dQw4w9WgXcQ) | {"license": "mit"} | itsroadtrip/test-pull-requests | null | [
"license:mit",
"region:us"
] | null | 2022-05-13T22:50:13+00:00 | [] | [] | TAGS
#license-mit #region-us
|
click me | [] | [
"TAGS\n#license-mit #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | gregtozzi/ppo-LunarLander-v2-2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T01:10:13+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | gregtozzi/ppo-LunarLander-v2-3 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T01:15:16+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | gregtozzi/ppo-LunarLander-v2-4 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T01:51:00+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-classification | transformers |
## Description
- Problem type: Binary Classification
## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837
## Usage
You can use cURL to access this model:
```
$ curl -X POST -H "Authorization: Bearer YOU... | {"language": "unk", "datasets": ["anwesham/autotrain-data-imdb-sentiment-analysis"]} | anwesham/imdb-sentiment-baseline-distilbert | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"unk",
"dataset:anwesham/autotrain-data-imdb-sentiment-analysis",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T02:06:07+00:00 | [] | [
"unk"
] | TAGS
#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #autotrain_compatible #endpoints_compatible #region-us
|
## Description
- Problem type: Binary Classification
## Validation Metrics
- Loss: 0.17481304705142975
- Accuracy: 0.936
- Precision: 0.9526578073089701
- Recall: 0.9176
- AUC: 0.9841454399999999
- F1: 0.93480032599837
## Usage
You can use cURL to access this model:
Or Python API:
| [
"## Description\n- Problem type: Binary Classification",
"## Validation Metrics\n- Loss: 0.17481304705142975\n- Accuracy: 0.936\n- Precision: 0.9526578073089701\n- Recall: 0.9176\n- AUC: 0.9841454399999999\n- F1: 0.93480032599837",
"## Usage\n\nYou can use cURL to access this model:\n\n\n\nOr Python API:"
] | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #autotrain_compatible #endpoints_compatible #region-us \n",
"## Description\n- Problem type: Binary Classification",
"## Validation Metrics\n- Loss: 0.17481304705142975\n- Accuracy: 0.936... |
text-classification | transformers |
- Problem type: Binary Classification
- Model ID: 864927559
- CO2 Emissions (in grams): 0.2033402242358345
## Validation Metrics
- Loss: 0.18383920192718506
- Accuracy: 0.9318
- Precision: 0.9560625264047318
- Recall: 0.9052
- AUC: 0.98281574
- F1: 0.9299363057324841
## Usage
You can use cURL to access this model:... | {"language": "unk", "datasets": ["anwesham/autotrain-data-imdb-sentiment-analysis"], "co2_eq_emissions": 0.2033402242358345} | anwesham/autotrain-imdb-sentiment-analysis-864927559 | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"unk",
"dataset:anwesham/autotrain-data-imdb-sentiment-analysis",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T02:06:26+00:00 | [] | [
"unk"
] | TAGS
#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us
|
- Problem type: Binary Classification
- Model ID: 864927559
- CO2 Emissions (in grams): 0.2033402242358345
## Validation Metrics
- Loss: 0.18383920192718506
- Accuracy: 0.9318
- Precision: 0.9560625264047318
- Recall: 0.9052
- AUC: 0.98281574
- F1: 0.9299363057324841
## Usage
You can use cURL to access this model:... | [
"## Validation Metrics\n\n- Loss: 0.18383920192718506\n- Accuracy: 0.9318\n- Precision: 0.9560625264047318\n- Recall: 0.9052\n- AUC: 0.98281574\n- F1: 0.9299363057324841",
"## Usage\n\nYou can use cURL to access this model:\n\n\n\nOr Python API:"
] | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #unk #dataset-anwesham/autotrain-data-imdb-sentiment-analysis #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us \n",
"## Validation Metrics\n\n- Loss: 0.18383920192718506\n- Accuracy: 0.9318\n- Precision: 0.9560625264047318\n- R... |
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... | sun1638650145/PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T02:52:31+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 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | send-it/TEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T02:57:11+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-classification | spacy | | Feature | Description |
| --- | --- |
| **Name** | `en_pipeline` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.1.4,<3.2.0` |
| **Default Pipeline** | `transformer`, `textcat` |
| **Components** | `transformer`, `textcat` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** ... | {"language": ["en"], "tags": ["spacy", "text-classification"], "model-index": [{"name": "en_pipeline", "results": []}]} | kangaroo927/en_pipeline | null | [
"spacy",
"text-classification",
"en",
"region:us"
] | null | 2022-05-14T03:29:58+00:00 | [] | [
"en"
] | TAGS
#spacy #text-classification #en #region-us
|
### Label Scheme
View label scheme (22 labels for 1 components)
### Accuracy
| [
"### Label Scheme\n\n\n\nView label scheme (22 labels for 1 components)",
"### Accuracy"
] | [
"TAGS\n#spacy #text-classification #en #region-us \n",
"### Label Scheme\n\n\n\nView label scheme (22 labels for 1 components)",
"### Accuracy"
] |
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. -->
# racism-finetuned-detests
This model is a fine-tuned version of [davidmasip/racism](https://huggingface.co/davidmasip/racism) on ... | {"license": "cc", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall"], "base_model": "davidmasip/racism", "model-index": [{"name": "racism-finetuned-detests", "results": []}]} | Pablo94/racism-finetuned-detests | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:davidmasip/racism",
"license:cc",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T03:56:57+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #base_model-davidmasip/racism #license-cc #autotrain_compatible #endpoints_compatible #region-us
| racism-finetuned-detests
========================
This model is a fine-tuned version of davidmasip/racism on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1626
* Accuracy: 0.8331
* F1-score: 0.7625
* Precision: 0.7625
* Recall: 0.7625
* Auc: 0.7625
Model description
--------... | [
"### 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: 10",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #base_model-davidmasip/racism #license-cc #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate:... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | NeonPigeon/TEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T04:31:06+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
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": []}]} | BitanBiswas/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 | 2022-05-14T04:46:49+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-timit-demo-google-colab
=====================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4770
* Wer: 0.3360
Model description
-----------------
More information needed
Intend... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8... |
null | keras | ## Model description
The original idea from [ResUNET++](https://arxiv.org/pdf/1911.07067.pdf)
Full credits go to [SynthesisHealthIntelligenceInc](https://synthesishealthinc.com/)
Ribs segmentation is a crucial step for removing the ribs before a diagnosis of x-ray images
## Dataset
[vindr-ribs](https://vindr.ai/datas... | {"library_name": "keras", "tags": ["xray-ribs-segmentation"]} | mostafapasha/ribs-segmentation-model | null | [
"keras",
"xray-ribs-segmentation",
"arxiv:1911.07067",
"has_space",
"region:us"
] | null | 2022-05-14T05:11:05+00:00 | [
"1911.07067"
] | [] | TAGS
#keras #xray-ribs-segmentation #arxiv-1911.07067 #has_space #region-us
| ## Model description
The original idea from ResUNET++
Full credits go to SynthesisHealthIntelligenceInc
Ribs segmentation is a crucial step for removing the ribs before a diagnosis of x-ray images
## Dataset
vindr-ribs | [
"## Model description\nThe original idea from ResUNET++\n\nFull credits go to SynthesisHealthIntelligenceInc\n\nRibs segmentation is a crucial step for removing the ribs before a diagnosis of x-ray images",
"## Dataset\nvindr-ribs"
] | [
"TAGS\n#keras #xray-ribs-segmentation #arxiv-1911.07067 #has_space #region-us \n",
"## Model description\nThe original idea from ResUNET++\n\nFull credits go to SynthesisHealthIntelligenceInc\n\nRibs segmentation is a crucial step for removing the ribs before a diagnosis of x-ray images",
"## Dataset\nvindr-rib... |
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. -->
# financial-sentiment-analysis
This model is a fine-tuned version of [ahmedrachid/FinancialBERT](https://huggingface.co/ahmedrachi... | {"tags": ["generated_from_trainer"], "datasets": ["financial_phrasebank"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "financial-sentiment-analysis", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "financial_phrasebank", "type": "financial_phraseban... | Sigma/financial-sentiment-analysis | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:financial_phrasebank",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-14T07:41:10+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-financial_phrasebank #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# financial-sentiment-analysis
This model is a fine-tuned version of ahmedrachid/FinancialBERT on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0395
- Accuracy: 0.9924
- F1: 0.9924
## Model description
More information needed
## Intended uses & limitations
... | [
"# financial-sentiment-analysis\n\nThis model is a fine-tuned version of ahmedrachid/FinancialBERT on the financial_phrasebank dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.0395\n- Accuracy: 0.9924\n- F1: 0.9924",
"## Model description\n\nMore information needed",
"## Intended us... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-financial_phrasebank #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# financial-sentiment-analysis\n\nThis model is a fine-tuned version of ahmedrachid/FinancialBERT on the ... |
fill-mask | transformers |
### Model description
- This model was trained on **ZH, JA, KO**'s Wikipedia (5 epochs).
### How to use
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("conan1024hao/cjkbert-small")
model = AutoModelForMaskedLM.from_pretrained("conan1024hao/cjkbert-smal... | {"language": ["ja", "zh", "ko"], "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "mask_token": "[MASK]", "widget": [{"text": "\u65e9\u7a32\u7530\u5927\u5b66\u3067\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u3092[MASK]\u3076\u3002"}, {"text": "\u674e\u767d\u662f[MASK]\u671d\u4eba\u3002"}, {"text": "\ubd88\uace0\uae30[MAS... | conan1024hao/cjkbert-small | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"ja",
"zh",
"ko",
"dataset:wikipedia",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T08:07:12+00:00 | [] | [
"ja",
"zh",
"ko"
] | TAGS
#transformers #pytorch #bert #fill-mask #ja #zh #ko #dataset-wikipedia #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
### Model description
- This model was trained on ZH, JA, KO's Wikipedia (5 epochs).
### How to use
- Before you fine-tune downstream tasks, you don't need any text segmentation.
- (Though you may obtain better results if you applied morphological analysis to the data before fine-tuning)
### Morphological analysis ... | [
"### Model description\n- This model was trained on ZH, JA, KO's Wikipedia (5 epochs).",
"### How to use\n\n- Before you fine-tune downstream tasks, you don't need any text segmentation.\n- (Though you may obtain better results if you applied morphological analysis to the data before fine-tuning)",
"### Morphol... | [
"TAGS\n#transformers #pytorch #bert #fill-mask #ja #zh #ko #dataset-wikipedia #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Model description\n- This model was trained on ZH, JA, KO's Wikipedia (5 epochs).",
"### How to use\n\n- Before you fine-tune downstream tasks, you... |
feature-extraction | sentence-transformers |
# sentence-transformers/paraphrase-multilingual-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becom... | {"license": "apache-2.0", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "feature-extraction"} | questgen/paraphrase-multilingual-mpnet-base-v2-feature-extraction-pipeline | null | [
"sentence-transformers",
"pytorch",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"arxiv:1908.10084",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T09:03:11+00:00 | [
"1908.10084"
] | [] | TAGS
#sentence-transformers #pytorch #xlm-roberta #feature-extraction #sentence-similarity #transformers #arxiv-1908.10084 #license-apache-2.0 #endpoints_compatible #region-us
|
# sentence-transformers/paraphrase-multilingual-mpnet-base-v2
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sen... | [
"# sentence-transformers/paraphrase-multilingual-mpnet-base-v2\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.",
"## Usage (Sentence-Transformers)\n\nUsing this model becomes easy when yo... | [
"TAGS\n#sentence-transformers #pytorch #xlm-roberta #feature-extraction #sentence-similarity #transformers #arxiv-1908.10084 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# sentence-transformers/paraphrase-multilingual-mpnet-base-v2\n\nThis is a sentence-transformers model: It maps sentences & paragr... |
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. -->
# Metformin/T5model_medFineTune
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an ... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "Metformin/T5model_medFineTune", "results": []}]} | Metformin/T5model_medFineTune | null | [
"transformers",
"tf",
"mt5",
"text2text-generation",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-14T09:11:14+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
| Metformin/T5model\_medFineTune
==============================
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: 9.0442
* Validation Loss: 6.1005
* Epoch: 9
Model description
-----------------
More information need... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'WarmUp', 'config': {'initial\\_learning\\_rate': 1e-05, 'decay\\_schedule\\_fn': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_le... | [
"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... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "c... | buehlpa/bert-finetuned-ner | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T09:38:18+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| bert-finetuned-ner
==================
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0607
* Precision: 0.9309
* Recall: 0.9493
* F1: 0.9400
* Accuracy: 0.9863
Model description
-----------------
More information ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nadirbekovnadir/LunarLander-278_18_2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T10:39:04+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nadirbekovnadir/LunarLander-278_18 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T10:40:01+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nadirbekovnadir/LunarLander-276_21 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T10:41:16+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | FumaNet/TEST1PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T10:53:17+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | FumaNet/TEST2PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T11:30:16+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | bartpotrykus/lunar-lander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T11:53:35+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
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. -->
# sber-full-test
This model is a fine-tuned version of [sberbank-ai/sbert_large_nlu_ru](https://huggingface.co/sberbank-ai/sbert_l... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "sber-full-test", "results": []}]} | ruselkomp/sber-full-test | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T11:57:24+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #endpoints_compatible #region-us
| sber-full-test
==============
This model is a fine-tuned version of sberbank-ai/sbert\_large\_nlu\_ru on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4148
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: 5\n* eval\\_batch\\_size: 5\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #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: 5\n* eval\\_batch\\_size: 5\n* seed:... |
text-generation | transformers |
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"text-generation",
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"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-14T12:21:58+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
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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/479663838896214016/nZtbm... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/dnouri/1652535050986/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/dnouri | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-14T12:23:53+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Daniel Nouri
@dnouri
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
------------... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-to-distilbert-NER
This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) o... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "model-index": [{"name": "bert-to-distilbert-NER", "results": []}]} | kushaljoseph/bert-to-distilbert-NER | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T12:24:58+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# bert-to-distilbert-NER
This model is a fine-tuned version of dslim/bert-base-NER on the conll2003 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.9063
- eval_precision: 0.0120
- eval_recall: 0.0069
- eval_f1: 0.0088
- eval_accuracy: 0.7600
- eval_runtime: 8.6309
- eval_samples_per... | [
"# bert-to-distilbert-NER\n\nThis model is a fine-tuned version of dslim/bert-base-NER on the conll2003 dataset.\nIt achieves the following results on the evaluation set:\n- eval_loss: 5.9063\n- eval_precision: 0.0120\n- eval_recall: 0.0069\n- eval_f1: 0.0088\n- eval_accuracy: 0.7600\n- eval_runtime: 8.6309\n- eval... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# bert-to-distilbert-NER\n\nThis model is a fine-tuned version of dslim/bert-base-NER on the conll2003 dataset.\nIt achieves t... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nadirbekovnadir/LunarLander-283_19 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T12:25:08+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-generation | transformers | # Fairseq-dense 13B - Nerys
## Model Description
Fairseq-dense 13B-Nerys is a finetune created using Fairseq's MoE dense model.
## Training data
The training data contains around 2500 ebooks in various genres (the "Pike" dataset), a CYOA dataset called "CYS" and 50 Asian "Light Novels" (the "Manga-v1" dataset).
Most pa... | {"language": "en", "license": "mit"} | KoboldAI/fairseq-dense-13B-Nerys | null | [
"transformers",
"pytorch",
"xglm",
"text-generation",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-14T12:31:19+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #xglm #text-generation #en #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us
| # Fairseq-dense 13B - Nerys
## Model Description
Fairseq-dense 13B-Nerys is a finetune created using Fairseq's MoE dense model.
## Training data
The training data contains around 2500 ebooks in various genres (the "Pike" dataset), a CYOA dataset called "CYS" and 50 Asian "Light Novels" (the "Manga-v1" dataset).
Most pa... | [
"# Fairseq-dense 13B - Nerys",
"## Model Description\nFairseq-dense 13B-Nerys is a finetune created using Fairseq's MoE dense model.",
"## Training data\nThe training data contains around 2500 ebooks in various genres (the \"Pike\" dataset), a CYOA dataset called \"CYS\" and 50 Asian \"Light Novels\" (the \"Man... | [
"TAGS\n#transformers #pytorch #xglm #text-generation #en #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# Fairseq-dense 13B - Nerys",
"## Model Description\nFairseq-dense 13B-Nerys is a finetune created using Fairseq's MoE dense model.",
"## Training data\nThe training da... |
summarization | 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. -->
# mbart-large-50-finetuned-persian
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook... | {"tags": ["summarization", "persian", "MBart50", "Abstractive Summarization", "generated_from_trainer"], "datasets": ["xlsum"], "model-index": [{"name": "mbart-large-50-finetuned-persian", "results": []}]} | ahmeddbahaa/mbart-large-50-finetuned-persian | null | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"summarization",
"persian",
"MBart50",
"Abstractive Summarization",
"generated_from_trainer",
"dataset:xlsum",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T12:40:15+00:00 | [] | [] | TAGS
#transformers #pytorch #mbart #text2text-generation #summarization #persian #MBart50 #Abstractive Summarization #generated_from_trainer #dataset-xlsum #autotrain_compatible #endpoints_compatible #region-us
| mbart-large-50-finetuned-persian
================================
This model is a fine-tuned version of facebook/mbart-large-50 on the xlsum dataset.
It achieves the following results on the evaluation set:
* Loss: 4.1932
* Rouge-1: 26.11
* Rouge-2: 8.11
* Rouge-l: 21.09
* Gen Len: 37.29
* Bertscore: 71.08
Model ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0005\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
"TAGS\n#transformers #pytorch #mbart #text2text-generation #summarization #persian #MBart50 #Abstractive Summarization #generated_from_trainer #dataset-xlsum #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\... |
fill-mask | 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. -->
# syp1229/roberta-base-finetuned-koidiom
This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-b... | {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "syp1229/roberta-base-finetuned-koidiom", "results": []}]} | syp1229/roberta-base-finetuned-koidiom | null | [
"transformers",
"tf",
"roberta",
"fill-mask",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T14:29:33+00:00 | [] | [] | TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us
| syp1229/roberta-base-finetuned-koidiom
======================================
This model is a fine-tuned version of klue/roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 2.5140
* Validation Loss: 2.0026
* Epoch: 0
Model description
-----------------
More... | [
"### 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 #roberta #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': 2e-05, 'decay': 0.0, ... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nadirbekovnadir/LunarLander-281_23 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T14:38:03+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-generation | transformers |
#DialoGPT with sebastian | {"tags": ["conversational"]} | THE-DDLM/DialoGPT-sebastian | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-14T14:54:42+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
#DialoGPT with sebastian | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text2text-generation | transformers |
This model is `mbart-large-50-many-to-many-mmt` model fine-tuned on the text part of [SLURP](https://github.com/pswietojanski/slurp) spoken language understanding dataset.
The scores on the test set are 85.68% and 79.00% for Intent accuracy and SLU-F1 respectively. | {"language": ["en"], "license": "apache-2.0", "tags": ["mbart-50"], "datasets": ["SLURP"], "metrics": ["accuracy", "slu-f1"]} | akreal/mbart-large-50-finetuned-slurp | null | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"mbart-50",
"en",
"dataset:SLURP",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T14:56:23+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #mbart #text2text-generation #mbart-50 #en #dataset-SLURP #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
This model is 'mbart-large-50-many-to-many-mmt' model fine-tuned on the text part of SLURP spoken language understanding dataset.
The scores on the test set are 85.68% and 79.00% for Intent accuracy and SLU-F1 respectively. | [] | [
"TAGS\n#transformers #pytorch #mbart #text2text-generation #mbart-50 #en #dataset-SLURP #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n"
] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.de"}, "me... | mubikan/xlm-roberta-base-finetuned-panx-de | null | [
"transformers",
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T14:57:44+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1383
* F1: 0.8589
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\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 #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_... |
reinforcement-learning | stable-baselines3 |
# **RPPO** Agent playing **CarRacing-v0**
This is a trained model of a **RPPO** agent playing **CarRacing-v0** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["CarRacing-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "RPPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CarRacing-v0", "type": "CarRacing... | DBusAI/RPPO-CarRacing-v0-v1 | null | [
"stable-baselines3",
"CarRacing-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T15:01:07+00:00 | [] | [] | TAGS
#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# RPPO Agent playing CarRacing-v0
This is a trained model of a RPPO agent playing CarRacing-v0 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# RPPO Agent playing CarRacing-v0\n This is a trained model of a RPPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #CarRacing-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# RPPO Agent playing CarRacing-v0\n This is a trained model of a RPPO agent playing CarRacing-v0 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add yo... |
fill-mask | 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. -->
# syp1229/koelectra-base-v3-generator-finetuned-koidiom
This model is a fine-tuned version of [monologg/koelectra-base-v3-generator](htt... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "syp1229/koelectra-base-v3-generator-finetuned-koidiom", "results": []}]} | syp1229/koelectra-base-v3-generator-finetuned-koidiom | null | [
"transformers",
"tf",
"electra",
"fill-mask",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T15:10:36+00:00 | [] | [] | TAGS
#transformers #tf #electra #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| syp1229/koelectra-base-v3-generator-finetuned-koidiom
=====================================================
This model is a fine-tuned version of monologg/koelectra-base-v3-generator on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 2.4310
* Validation Loss: 2.0533
* Epoc... | [
"### 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 #electra #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': 2... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **FrozenLake-v1**
This is a trained model of a **PPO** agent playing **FrozenLake-v1** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["FrozenLake-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1", "type": "FrozenLa... | Tanchik/TESTppo_FrozenLake-v1 | null | [
"stable-baselines3",
"FrozenLake-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T15:16:44+00:00 | [] | [] | TAGS
#stable-baselines3 #FrozenLake-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing FrozenLake-v1
This is a trained model of a PPO agent playing FrozenLake-v1 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing FrozenLake-v1\n This is a trained model of a PPO agent playing FrozenLake-v1 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #FrozenLake-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing FrozenLake-v1\n This is a trained model of a PPO agent playing FrozenLake-v1 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add y... |
image-classification | transformers |
# Vision Transformer fine-tuned on `Matthijs/snacks` dataset
Vision Transformer (ViT) model pre-trained on ImageNet-21k and fine-tuned on [**Matthijs/snacks**](https://huggingface.co/datasets/Matthijs/snacks) for 5 epochs using various data augmentation transformations from `torchvision`.
The model achieves a **94.9... | {"datasets": ["Matthijs/snacks"], "model-index": [{"name": "matteopilotto/vit-base-patch16-224-in21k-snacks", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "Matthijs/snacks", "type": "Matthijs/snacks", "config": "default", "split": "test"}, "metrics": [{"type... | matteopilotto/vit-base-patch16-224-in21k-snacks | null | [
"transformers",
"pytorch",
"vit",
"image-classification",
"dataset:Matthijs/snacks",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T15:23:18+00:00 | [] | [] | TAGS
#transformers #pytorch #vit #image-classification #dataset-Matthijs/snacks #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# Vision Transformer fine-tuned on 'Matthijs/snacks' dataset
Vision Transformer (ViT) model pre-trained on ImageNet-21k and fine-tuned on Matthijs/snacks for 5 epochs using various data augmentation transformations from 'torchvision'.
The model achieves a 94.97% and 94.43% accuracy on the validation and test set, re... | [
"# Vision Transformer fine-tuned on 'Matthijs/snacks' dataset\n\nVision Transformer (ViT) model pre-trained on ImageNet-21k and fine-tuned on Matthijs/snacks for 5 epochs using various data augmentation transformations from 'torchvision'.\n\nThe model achieves a 94.97% and 94.43% accuracy on the validation and test... | [
"TAGS\n#transformers #pytorch #vit #image-classification #dataset-Matthijs/snacks #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# Vision Transformer fine-tuned on 'Matthijs/snacks' dataset\n\nVision Transformer (ViT) model pre-trained on ImageNet-21k and fine-tuned on Matthijs/snacks f... |
automatic-speech-recognition | transformers |
# Wav2Vec2-base-fi-voxpopuli-v2 for Finnish ASR
This acoustic model is a fine-tuned version of [facebook/wav2vec2-base-fi-voxpopuli-v2](https://huggingface.co/facebook/wav2vec2-base-fi-voxpopuli-v2) for Finnish ASR. The model has been fine-tuned with 276.7 hours of Finnish transcribed speech data. Wav2Vec2 was introd... | {"language": "fi", "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fi", "finnish", "generated_from_trainer", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_9_0"], "metrics": ["wer", "cer"], "model-index": [{"name": "wav2vec2-base-fi-voxpopuli-v2-finetuned", "results": [{"task": ... | Finnish-NLP/wav2vec2-base-fi-voxpopuli-v2-finetuned | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"fi",
"finnish",
"generated_from_trainer",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_9_0",
"arxiv:2006.11477",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_spac... | null | 2022-05-14T15:30:58+00:00 | [
"2006.11477"
] | [
"fi"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #fi #finnish #generated_from_trainer #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_9_0 #arxiv-2006.11477 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Wav2Vec2-base-fi-voxpopuli-v2 for Finnish ASR
=============================================
This acoustic model is a fine-tuned version of facebook/wav2vec2-base-fi-voxpopuli-v2 for Finnish ASR. The model has been fine-tuned with 276.7 hours of Finnish transcribed speech data. Wav2Vec2 was introduced in
this paper an... | [
"### How to use\n\n\nCheck the URL notebook in this repository for an detailed example on how to use this model.",
"### Limitations and bias\n\n\nThis model was fine-tuned with audio samples which maximum length was 20 seconds so this model most likely works the best for quite short audios of similar length. Howe... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #fi #finnish #generated_from_trainer #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_9_0 #arxiv-2006.11477 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"### How to use\n\n\nCheck th... |
null | keras |
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training Metrics
Model history needed
## Model Plot
<details>
<summary>View Model Plot</summary>
</details> | {"library_name": "keras"} | Rietta/CycleGAN_Sims | null | [
"keras",
"region:us"
] | null | 2022-05-14T15:36:02+00:00 | [] | [] | TAGS
#keras #region-us
|
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training Metrics
Model history needed
## Model Plot
<details>
<summary>View Model Plot</summary>
!Model Image
</details> | [
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed\n\n ## Training Metrics\nModel history needed\n ## Model Plot\n\n<details>\n<summary>View Model Plot</summary>\n\n!Model Image\n\n</details>... | [
"TAGS\n#keras #region-us \n",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed\n\n ## Training Metrics\nModel history needed\n ## Model Plot\n\n<details>\n<summary>View Model Plot</summar... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **CartPole-v1**
This is a trained model of a **PPO** agent playing **CartPole-v1** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["CartPole-v1", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"... | meln1k/ppo-CartPole-v1 | null | [
"stable-baselines3",
"CartPole-v1",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T15:37:31+00:00 | [] | [] | TAGS
#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing CartPole-v1
This is a trained model of a PPO agent playing CartPole-v1 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing CartPole-v1\n This is a trained model of a PPO agent playing CartPole-v1 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #CartPole-v1 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing CartPole-v1\n This is a trained model of a PPO agent playing CartPole-v1 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your co... |
fill-mask | 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. -->
# nouman10/robertabase-finetuned-claim-ltp
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on ... | {"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "nouman10/robertabase-finetuned-claim-ltp", "results": []}]} | nouman10/robertabase-finetuned-claim-ltp | null | [
"transformers",
"tf",
"roberta",
"fill-mask",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T15:38:16+00:00 | [] | [] | TAGS
#transformers #tf #roberta #fill-mask #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us
| nouman10/robertabase-finetuned-claim-ltp
========================================
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.0790
* Validation Loss: 0.0631
* Epoch: 4
Model description
-----------------
More ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'inner\\_optimizer': {'class\\_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'WarmUp', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_schedule... | [
"TAGS\n#transformers #tf #roberta #fill-mask #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'inner\\_optimizer': {'class\\_name': 'AdamWeightDecay... |
fill-mask | 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. -->
# syp1229/bert-base-finetuned-koidiom
This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on a... | {"tags": ["generated_from_keras_callback"], "model-index": [{"name": "syp1229/bert-base-finetuned-koidiom", "results": []}]} | syp1229/bert-base-finetuned-koidiom | null | [
"transformers",
"tf",
"bert",
"fill-mask",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T15:42:21+00:00 | [] | [] | TAGS
#transformers #tf #bert #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us
| syp1229/bert-base-finetuned-koidiom
===================================
This model is a fine-tuned version of klue/bert-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 2.1288
* Validation Loss: 1.8307
* Epoch: 0
Model description
-----------------
More informat... | [
"### 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 #bert #fill-mask #generated_from_keras_callback #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': 2e-05, 'decay': 0.0, 'be... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | nadirbekovnadir/LunarLander-280_20 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T15:52:45+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-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"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": []}]} | Leizhang/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T15:53:40+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #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.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
... | [
"# distilbert-base-uncased-finetuned-emotion\n\nThis model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# distilbert-base-uncased-finetuned-emotion\n\nThis model is a fine-tuned version of distilbert-base-uncased on the ... |
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... | 0x05a4/DeepRL-PPO-LLv2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T15:54:28+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 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | memorysaver/TEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T16:01:33+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | memorysaver/ppo-LunarLander-v2-2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T16:43:05+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
text-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/1082744382585856001/rH_k... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/spacex/1652551333667/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/spacex | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-14T16:51:44+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
SpaceX
@spacex
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
-------------
Th... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# NER-CoNLL2003-V3
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unk... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "NER-CoNLL2003-V3", "results": []}]} | Xiaoman/NER-CoNLL2003-V3 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T17:02:26+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# NER-CoNLL2003-V3
This model is a fine-tuned version of bert-large-uncased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
T... | [
"# NER-CoNLL2003-V3\n\nThis model is a fine-tuned version of bert-large-uncased on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"#... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# NER-CoNLL2003-V3\n\nThis model is a fine-tuned version of bert-large-uncased on an unknown dataset.",
"## Model description\n\nMore in... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xtreme"], "metrics": ["f1"], "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "xtreme", "type": "xtreme", "args": "PAN-X.de"}, "me... | claytonsamples/xlm-roberta-base-finetuned-panx-de | null | [
"transformers",
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"dataset:xtreme",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T17:40:01+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on the xtreme dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1372
* F1: 0.8621
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 24\n* eval\\_batch\\_size: 24\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 #xlm-roberta #token-classification #generated_from_trainer #dataset-xtreme #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_... |
reinforcement-learning | stable-baselines3 |
# **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).
## Usage (with Stable-baselines3)
```python
from huggingface_sb3 import load_from_hub
from sb3_contrib import ... | {"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... | araffin/tqc-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-14T17:47:28+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.
## Usage (with Stable-baselines3)
## Training code (with SB3)
| [
"# TQC Agent playing BipedalWalker-v3\n This is a trained model of a TQC agent playing BipedalWalker-v3 using the stable-baselines3 library.",
"## Usage (with Stable-baselines3)",
"## Training code (with SB3)"
] | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# TQC Agent playing BipedalWalker-v3\n This is a trained model of a TQC agent playing BipedalWalker-v3 using the stable-baselines3 library.",
"## Usage (with Stable-baselines3)",
"##... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# NER-CoNLL2003-V4
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unk... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "NER-CoNLL2003-V4", "results": []}]} | Xiaoman/NER-CoNLL2003-V4 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T17:52:51+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| NER-CoNLL2003-V4
================
This model is a fine-tuned version of bert-large-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2095
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More i... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7.961395091713594e-05\n* train\\_batch\\_size: 6\n* eval\\_batch\\_size: 6\n* seed: 27\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7.961395091713594e-05\n... |
question-answering | transformers | Multilingual MiniLMv2 fine-tuned using Knowledge Distillation with a XLM Roberta Base Teacher Model on ZH Language | {} | subhasisj/zh-kd-XLM-minilmv2-4 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"question-answering",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:07:20+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #question-answering #endpoints_compatible #region-us
| Multilingual MiniLMv2 fine-tuned using Knowledge Distillation with a XLM Roberta Base Teacher Model on ZH Language | [] | [
"TAGS\n#transformers #pytorch #tensorboard #bert #question-answering #endpoints_compatible #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. -->
# hubert-base-libri-clean-ft100h
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/faceboo... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["librispeech_asr"], "model-index": [{"name": "hubert-base-libri-clean-ft100h", "results": []}]} | danieleV9H/hubert-base-libri-clean-ft100h | null | [
"transformers",
"pytorch",
"tensorboard",
"hubert",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:librispeech_asr",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:09:33+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #hubert #automatic-speech-recognition #generated_from_trainer #dataset-librispeech_asr #license-apache-2.0 #endpoints_compatible #region-us
| hubert-base-libri-clean-ft100h
==============================
This model is a fine-tuned version of facebook/hubert-base-ls960 on the librispeech\_asr dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1324
* Wer: 0.1597
Model description
-----------------
More information needed
Inte... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
"TAGS\n#transformers #pytorch #tensorboard #hubert #automatic-speech-recognition #generated_from_trainer #dataset-librispeech_asr #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* t... |
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. -->
# roberta-large-few-shot-k-16-finetuned-squad-seed-0
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-16-finetuned-squad-seed-0", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-16-finetuned-squad-seed-0 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:13:38+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-16-finetuned-squad-seed-0
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-16-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-16-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-16-finetuned-squad-seed-0
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-16-finetuned-squad-seed-0", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-16-finetuned-squad-seed-0 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:17:23+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-16-finetuned-squad-seed-0
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-16-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-16-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-16-finetuned-squad-seed-2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-16-finetuned-squad-seed-2", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-16-finetuned-squad-seed-2 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:23:44+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-16-finetuned-squad-seed-2
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-16-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-16-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-16-finetuned-squad-seed-2
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-16-finetuned-squad-seed-2", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-16-finetuned-squad-seed-2 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:27:14+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-16-finetuned-squad-seed-2
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-16-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-16-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-16-finetuned-squad-seed-4
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-16-finetuned-squad-seed-4", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-16-finetuned-squad-seed-4 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:33:24+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-16-finetuned-squad-seed-4
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-16-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-16-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-16-finetuned-squad-seed-4
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-16-finetuned-squad-seed-4", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-16-finetuned-squad-seed-4 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:37:07+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-16-finetuned-squad-seed-4
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-16-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-16-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-32-finetuned-squad-seed-0
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-32-finetuned-squad-seed-0", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-32-finetuned-squad-seed-0 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:43:48+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-32-finetuned-squad-seed-0
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-32-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-32-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-32-finetuned-squad-seed-0
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-32-finetuned-squad-seed-0", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-32-finetuned-squad-seed-0 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:47:36+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-32-finetuned-squad-seed-0
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-32-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-32-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-32-finetuned-squad-seed-2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-32-finetuned-squad-seed-2", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-32-finetuned-squad-seed-2 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:54:13+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-32-finetuned-squad-seed-2
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-32-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-32-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-32-finetuned-squad-seed-2
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-32-finetuned-squad-seed-2", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-32-finetuned-squad-seed-2 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T18:58:04+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-32-finetuned-squad-seed-2
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-32-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-32-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-32-finetuned-squad-seed-4
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-32-finetuned-squad-seed-4", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-32-finetuned-squad-seed-4 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T19:04:35+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-32-finetuned-squad-seed-4
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-32-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-32-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-32-finetuned-squad-seed-4
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-32-finetuned-squad-seed-4", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-32-finetuned-squad-seed-4 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T19:08:23+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-32-finetuned-squad-seed-4
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-32-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-32-finetuned-squad-seed-4\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-64-finetuned-squad-seed-0
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-64-finetuned-squad-seed-0", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-64-finetuned-squad-seed-0 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T19:15:19+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-64-finetuned-squad-seed-0
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-64-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-64-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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. -->
# splinter-large-few-shot-k-64-finetuned-squad-seed-0
This model is a fine-tuned version of [tau/splinter-large-qass](https://hugg... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "splinter-large-few-shot-k-64-finetuned-squad-seed-0", "results": []}]} | anas-awadalla/splinter-large-few-shot-k-64-finetuned-squad-seed-0 | null | [
"transformers",
"pytorch",
"splinter",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T19:19:39+00:00 | [] | [] | TAGS
#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# splinter-large-few-shot-k-64-finetuned-squad-seed-0
This model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training pro... | [
"# splinter-large-few-shot-k-64-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information n... | [
"TAGS\n#transformers #pytorch #splinter #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# splinter-large-few-shot-k-64-finetuned-squad-seed-0\n\nThis model is a fine-tuned version of tau/splinter-large-qass on the squad dataset.",
"## Model d... |
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. -->
# roberta-large-few-shot-k-64-finetuned-squad-seed-2
This model is a fine-tuned version of [roberta-large](https://huggingface.co/... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-large-few-shot-k-64-finetuned-squad-seed-2", "results": []}]} | anas-awadalla/roberta-large-few-shot-k-64-finetuned-squad-seed-2 | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-14T19:25:43+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
|
# roberta-large-few-shot-k-64-finetuned-squad-seed-2
This model is a fine-tuned version of roberta-large on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
###... | [
"# roberta-large-few-shot-k-64-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"... | [
"TAGS\n#transformers #pytorch #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"# roberta-large-few-shot-k-64-finetuned-squad-seed-2\n\nThis model is a fine-tuned version of roberta-large on the squad dataset.",
"## Model description\n\nMore ... |
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