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question-answering | 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. -->
# vanichandna/indic-bert-finetuned-squad
This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/i... | {"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "vanichandna/indic-bert-finetuned-squad", "results": []}]} | vanichandna/indic-bert-finetuned-squad | null | [
"transformers",
"tf",
"albert",
"question-answering",
"generated_from_keras_callback",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T19:11:36+00:00 | [] | [] | TAGS
#transformers #tf #albert #question-answering #generated_from_keras_callback #license-mit #endpoints_compatible #region-us
| vanichandna/indic-bert-finetuned-squad
======================================
This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 1.0802
* Epoch: 3
Model description
-----------------
More information needed
I... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_steps': 21984, 'end\\_learning\\_rate': 0.0, 'power': 1.0, 'cycle':... | [
"TAGS\n#transformers #tf #albert #question-answering #generated_from_keras_callback #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'Poly... |
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... | jabot/PPPO_LunarLanderV2_1000000Steps_schLR_schCR | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T19:13:04+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... | nkt32/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T19:15:58+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... |
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... | melodisease/ppo-LunarLander-v2-steps-2kk | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T19:34:51+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-base-finetuned-scrambled-squad-5-new
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-base-finetuned-scrambled-squad-5-new", "results": []}]} | huxxx657/roberta-base-finetuned-scrambled-squad-5-new | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T19:39:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
| roberta-base-finetuned-scrambled-squad-5-new
============================================
This model is a fine-tuned version of roberta-base on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9098
Model description
-----------------
More information needed
Intended uses &... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 16\n*... |
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. -->
# ar-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": "ar-TAPT-MLM-MiniLM", "results": []}]} | subhasisj/ar-TAPT-MLM-MiniLM | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T19:39:20+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
|
# ar-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... | [
"# ar-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",
"# ar-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... | tjscollins/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T19:45:13+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... |
text-generation | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# KenP/codeparrot-ds
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the fo... | {"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "KenP/codeparrot-ds", "results": []}]} | KenP/codeparrot-ds | null | [
"transformers",
"tf",
"gpt2",
"text-generation",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-10T19:46:24+00:00 | [] | [] | TAGS
#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| KenP/codeparrot-ds
==================
This model is a fine-tuned version of gpt2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 10.3900
* Validation Loss: 9.6171
* Epoch: 0
Model description
-----------------
More information needed
Intended uses & limitations
--... | [
"### 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': 5e-05, 'decay\\_schedule\\_fn': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_le... | [
"TAGS\n#transformers #tf #gpt2 #text-generation #generated_from_keras_callback #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* optimizer: {'name': 'AdamWeightDecay... |
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... | FollishBoi/ppo-LunarLander-v2-try5 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T19:49:01+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... | tomascufaro/lunarlander-model-v1 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T19:51:02+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 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T20:03:07+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
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. -->
# distilbart-cnn-arxiv-pubmed-pubmed-v3-e8
This model is a fine-tuned version of [theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed]... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "distilbart-cnn-arxiv-pubmed-pubmed-v3-e8", "results": []}]} | theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed-v3-e8 | null | [
"transformers",
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T20:27:07+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbart-cnn-arxiv-pubmed-pubmed-v3-e8
========================================
This model is a fine-tuned version of theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8422
* Rouge1: 54.9328
* Rouge2: 36.7154
* Rougel: 39.5674... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 8\n* mixed\\_precis... | [
"TAGS\n#transformers #pytorch #tensorboard #bart #text2text-generation #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: 2e-05\n* train\\_batch\... |
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... | fminichev/TEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T20:40:24+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... | tomascufaro/lunarlander-model-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T20:44:09+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... | bguan/lunar_lander_v2_ppo_5 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T20:52:11+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... |
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... | mustapha/Lunar_lander_v2_gym | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T20:54:22+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 | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | fastai/blurr_IMDB_bert_classification | null | [
"fastai",
"region:us"
] | null | 2022-05-10T21:01:53+00:00 | [] | [] | TAGS
#fastai #region-us
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentation here).\n\n3. Join the fastai co... | [
"TAGS\n#fastai #region-us \n",
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentatio... |
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. -->
# mt5-base-finetuned-english
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on th... | {"license": "apache-2.0", "tags": ["summarization", "english", "en", "mt5", "Abstractive Summarization", "generated_from_trainer"], "datasets": ["xlsum"], "model-index": [{"name": "mt5-base-finetuned-english", "results": []}]} | eslamxm/mt5-base-finetuned-english | null | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"summarization",
"english",
"en",
"Abstractive Summarization",
"generated_from_trainer",
"dataset:xlsum",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-10T21:05:49+00:00 | [] | [] | TAGS
#transformers #pytorch #mt5 #text2text-generation #summarization #english #en #Abstractive Summarization #generated_from_trainer #dataset-xlsum #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| mt5-base-finetuned-english
==========================
This model is a fine-tuned version of google/mt5-base on the xlsum dataset.
It achieves the following results on the evaluation set:
* Loss: 3.3271
* Rouge-1: 31.7
* Rouge-2: 11.83
* Rouge-l: 26.43
* Gen Len: 18.88
* Bertscore: 74.3
Model description
---------... | [
"### 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 #mt5 #text2text-generation #summarization #english #en #Abstractive Summarization #generated_from_trainer #dataset-xlsum #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperpa... |
text2text-generation | transformers |
<p align="center">
<br>
<img src="https://github.com/UBC-NLP/turjuman/raw/master//images/turjuman_logo.png"/>
<br>
<p>
<img src="https://github.com/UBC-NLP/turjuman/raw/master/images/turjuman.png" alt="AraT5" width="50%" height="50%" align="right"/>
Turjuman is a neural machine translation tool... | {} | UBC-NLP/turjuman | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"arxiv:2206.03933",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-10T21:07:50+00:00 | [
"2206.03933"
] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #arxiv-2206.03933 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<p align="center">
<br>
<img src="URL/images/turjuman_logo.png"/>
<br>
<p>
<img src="URL alt="AraT5" width="50%" height="50%" align="right"/>
Turjuman is a neural machine translation toolkit. It translates from 20 languages into Modern Standard Arabic (MSA). Turjuman is described in this paper:... | [
"## License\nturjuman(-py) is Apache-2.0 licensed. The license applies to the pre-trained models as well.\n\nIf you use TURJUMAN toolkit or the pre-trained models for your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows (to be updated):"
] | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #arxiv-2206.03933 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## License\nturjuman(-py) is Apache-2.0 licensed. The license applies to the pre-trained models as well.\n\nIf you use TURJUMAN toolkit or the pre-train... |
null | fastai |
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit using 🤗 Spaces ([docume... | {"tags": ["fastai"]} | fastai/blurr_IMDB_distilbert_classification | null | [
"fastai",
"region:us"
] | null | 2022-05-10T21:11:18+00:00 | [] | [] | TAGS
#fastai #region-us
|
# Amazing!
Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the documentation here)!
2. Create a demo in Gradio or Streamlit using Spaces (documentation here).
3. Join the fastai community on the ... | [
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentation here).\n\n3. Join the fastai co... | [
"TAGS\n#fastai #region-us \n",
"# Amazing!\n\n Congratulations on hosting your fastai model on the Hugging Face Hub!",
"# Some next steps\n1. Fill out this model card with more information (see the template below and the documentation here)!\n\n2. Create a demo in Gradio or Streamlit using Spaces (documentatio... |
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-base-finetuned-scrambled-squad-10-new
This model is a fine-tuned version of [roberta-base](https://huggingface.co/robert... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-base-finetuned-scrambled-squad-10-new", "results": []}]} | huxxx657/roberta-base-finetuned-scrambled-squad-10-new | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T21:49:53+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
| roberta-base-finetuned-scrambled-squad-10-new
=============================================
This model is a fine-tuned version of roberta-base on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9721
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 16\n*... |
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. -->
# madatnlp/mt5-kormath
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown d... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "madatnlp/mt5-kormath", "results": []}]} | madatnlp/mt5-kormath | null | [
"transformers",
"tf",
"mt5",
"text2text-generation",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-10T21:55:04+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
| madatnlp/mt5-kormath
====================
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: 0.7119
* Validation Loss: 1.1299
* Epoch: 61
Model description
-----------------
More information needed
Intended uses ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 0.001, 'decay': 0.0, 'beta\\_1': 0.9, 'beta\\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}\n* training\\_precision: mixed\\_bfloat16",
"### Training results",
"### ... | [
"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... |
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... | liuzhenqi77/LunarLander-SB3-PPO-test-1 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:04:00+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
| {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | FollishBoi/ppo-LunarLander-v2-try6 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:13:21+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... | FollishBoi/ppo-LunarLander-v2-try7 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:17:10+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... |
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... | FollishBoi/ppo-LunarLander-v2-try3 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:19:28+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 |
# **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... | FollishBoi/ppo-LunarLander-v2-try8 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:23:03+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... |
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... | FollishBoi/ppo-LunarLander-v2-try9 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:25:05+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... |
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... | FollishBoi/ppo-LunarLander-v2-try10 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:26:31+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\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... | FollishBoi/ppo-LunarLander-v2-try11 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:29:22+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 | precision recall f1-score support
negative 0.733238 0.778788 0.755327 660
neutral 0.757962 0.779963 0.768805 1068
positive 0.722793 0.728778 0.725773 483
skip 0.660714 0.501355 0.570108 369
speech 0.767857 0.868687 0.815166 ... | {} | sismetanin/ruroberta-ru-rusentitweet | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"doi:10.57967/hf/0103",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T22:33:17+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #text-classification #doi-10.57967/hf/0103 #autotrain_compatible #endpoints_compatible #region-us
| precision recall f1-score support
negative 0.733238 0.778788 0.755327 660
neutral 0.757962 0.779963 0.768805 1068
positive 0.722793 0.728778 0.725773 483
skip 0.660714 0.501355 0.570108 369
speech 0.767857 0.868687 0.815166 ... | [] | [
"TAGS\n#transformers #pytorch #roberta #text-classification #doi-10.57967/hf/0103 #autotrain_compatible #endpoints_compatible #region-us \n"
] |
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... | mindwrapped/ppo-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T22:46:10+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... | pm3512/TEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-10T23:35:40+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-base-finetuned-scrambled-squad-15-new
This model is a fine-tuned version of [roberta-base](https://huggingface.co/robert... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "roberta-base-finetuned-scrambled-squad-15-new", "results": []}]} | huxxx657/roberta-base-finetuned-scrambled-squad-15-new | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-05-10T23:59:03+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us
| roberta-base-finetuned-scrambled-squad-15-new
=============================================
This model is a fine-tuned version of roberta-base on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0283
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 16\n*... |
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. -->
# distilgpt2_fine_tuned_gcode
This model is a fine-tuned version of [congcongwang/distilgpt2_fine_tuned_coder](https://huggingface... | {"tags": ["generated_from_trainer"], "model-index": [{"name": "distilgpt2_fine_tuned_gcode", "results": []}]} | ablam/distilgpt2_fine_tuned_gcode | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T00:09:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| distilgpt2\_fine\_tuned\_gcode
==============================
This model is a fine-tuned version of congcongwang/distilgpt2\_fine\_tuned\_coder on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 4.1670
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.1\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: 1",
"### Training r... | [
"TAGS\n#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #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: 0.1\n* train\\_batch\... |
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/1244518578537160704/ZWf8... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/cdrsuperheroga1/1652231741388/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/cdrsuperheroga1 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T00:14:50+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
cdrsuperhero\_gaming
@cdrsuperheroga1
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training ... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **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... | koala978/PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T00:24:41+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... | nahumsa/ppo1-LunarLander-v2-2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T00:48:58+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... |
text-generation | transformers |
[千言—AdvertiseGen广告文案生成数据集](https://www.luge.ai/#/luge/dataDetail?id=9)
> 仅支持.bin(pytorch)
在该千言数据集微调了5个epoch，
```python
input_text = '类型#裙*材质#针织*风格#简约*风格#青春*风格#清新*风格#性感*图案#条纹*图案#撞色*裙下摆#开叉*裙长#连衣裙*裙款式#拼接*裙款式#吊带'
output_text = gen_ads(input_text)
output_text = output_text.replace(' ', '')
output_text = output_te... | {"license": "apache-2.0"} | cocoshe/gpt2-chinese-gen-ads-by-keywords | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T01:09:28+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
千言—AdvertiseGen广告文案生成数据集
> 仅支持.bin(pytorch)
在该千言数据集微调了5个epoch，
输出(实际中注意控制max_length)
| [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flat_N_max
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on th... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "flat_N_max", "results": []}]} | mcurmei/flat_N_max | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T01:17:54+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| flat\_N\_max
============
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8536
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More inform... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval... |
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... | yomexa/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 | 2022-05-11T01:19:27+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 |
# **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... | ogabrielluiz/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T01:23:42+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... | jonporterjones/TEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T01:51:25+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. -->
# NER_EHR_Spanish_model_Mulitlingual_BERT
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "widget": [{"text": "Presentamos el caso de una mujer de 30 a\u00f1os, fumadora de 20 cigarrillos/d\u00eda y sin otros antecedentes personales de inter\u00e9s. La paciente refiere infecciones urinarias de... | ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T01:54:02+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| NER\_EHR\_Spanish\_model\_Mulitlingual\_BERT
============================================
This model is a fine-tuned version of bert-base-multilingual-cased on the DisTEMIST shared task 2022 dataset. It is available at: URL
It achieves the following results on the evaluation set:
* Loss: 0.2603
* Precision: 0.563... | [
"### 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: 7",
"### Training... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #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\n* tra... |
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... | kirk123/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T02:03:53+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... |
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. -->
# single_label_N_max
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncase... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "single_label_N_max", "results": []}]} | mcurmei/single_label_N_max | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T03:19:42+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
| single\_label\_N\_max
=====================
This model is a fine-tuned version of distilbert-base-uncased on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.9326
Model description
-----------------
More information needed
Intended uses & limitations
----------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_s... |
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... | bbhaskar8/PPO-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T03:31:49+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... | fatPegasus23/TesLunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T03:55:44+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... |
text2text-generation | transformers | SalamaThanks Transformer for English-to-Filipino Text Translation version 1.
Based on the Helsinki-NLP/opus-mt-en-tl transformer model. | {"license": "afl-3.0"} | SalamaThanks/SalamaThanksTransformer_en2fil_v1 | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T04:31:27+00:00 | [] | [] | TAGS
#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| SalamaThanks Transformer for English-to-Filipino Text Translation version 1.
Based on the Helsinki-NLP/opus-mt-en-tl transformer model. | [] | [
"TAGS\n#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
text2text-generation | transformers | SalamaThanks Transformer for Filipino-to-English Text Translation version 1.
Based on the Helsinki-NLP/opus-mt-tl-en transformer model. | {"license": "afl-3.0"} | SalamaThanks/SalamaThanksTransformer_fil2en_v1 | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T04:34:45+00:00 | [] | [] | TAGS
#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| SalamaThanks Transformer for Filipino-to-English Text Translation version 1.
Based on the Helsinki-NLP/opus-mt-tl-en transformer model. | [] | [
"TAGS\n#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
text2text-generation | transformers | SalamaThanks Transformer for English-to-Filipino Text Translation version 2.
A finetuned transformer model based on the Helsinki-NLP/opus-mt-en-tl transformer model. | {"license": "afl-3.0"} | SalamaThanks/SalamaThanksTransformer_en2fil_v2 | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T04:39:27+00:00 | [] | [] | TAGS
#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| SalamaThanks Transformer for English-to-Filipino Text Translation version 2.
A finetuned transformer model based on the Helsinki-NLP/opus-mt-en-tl transformer model. | [] | [
"TAGS\n#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
text2text-generation | transformers | SalamaThanks Transformer for Filipino-to-English Text Translation version 2.
A finetuned model based on the Helsinki-NLP/opus-mt-en-tl transformer model. | {"license": "afl-3.0"} | SalamaThanks/SalamaThanksTransformer_fil2en_v2 | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T04:42:28+00:00 | [] | [] | TAGS
#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| SalamaThanks Transformer for Filipino-to-English Text Translation version 2.
A finetuned model based on the Helsinki-NLP/opus-mt-en-tl transformer model. | [] | [
"TAGS\n#transformers #pytorch #marian #text2text-generation #license-afl-3.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# unique_N_max
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "unique_N_max", "results": []}]} | mcurmei/unique_N_max | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T04:54:58+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| unique\_N\_max
==============
This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7409
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More in... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval... |
sentence-similarity | sentence-transformers |
# {MODEL_NAME}
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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | ceggian/sbert_standard_reddit_mnr | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T05:23:01+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# {MODEL_NAME}
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 sentence-transformers installed:
Then you can u... | [
"# {MODEL_NAME}\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 you have sentence-transformers installed:\n\n\n\n... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# {MODEL_NAME}\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 se... |
text-generation | transformers |
# German GPT2-XL (1.5B)
- trained with [BigScience's DeepSpeed-Megatron-LM code base](https://github.com/bigscience-workshop/Megatron-DeepSpeed)
- word embedding initialized with [WECHSEL](https://arxiv.org/abs/2112.06598) and all other weights taken from English [gpt2-xl](https://huggingface.co/gpt2-xl)
- ~ 3 days o... | {"language": "de", "license": "mit", "pipeline_tag": "text-generation", "widget": [{"text": "In einer schockierenden Entdeckung fanden Wissenschaftler eine Herde Einh\u00f6rner, die in ", "example_title": "Einh\u00f6rner ..."}, {"text": "Definiere folgende W\u00f6rter\n\nWort: Einhorn\nDefinition: Das Einhorn ist ein F... | malteos/gpt2-xl-wechsel-german | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"de",
"arxiv:2112.06598",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T05:24:56+00:00 | [
"2112.06598"
] | [
"de"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #de #arxiv-2112.06598 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| German GPT2-XL (1.5B)
=====================
* trained with BigScience's DeepSpeed-Megatron-LM code base
* word embedding initialized with WECHSEL and all other weights taken from English gpt2-xl
* ~ 3 days on 16xA100 GPUs (~ 80 TFLOPs / GPU)
* stopped after 100k steps
* 26.2B tokens
* less than a single epoch on 'osc... | [
"### How to use\n\n\nYou can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we\nset a seed for reproducibility:\n\n\nHere is how to use this model to get the features of a given text in PyTorch:\n\n\nEvaluation\n----------\n\n\n\nOther German language mo... | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #de #arxiv-2112.06598 #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### How to use\n\n\nYou can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, w... |
sentence-similarity | sentence-transformers |
# {MODEL_NAME}
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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | ceggian/sbert_standard_reddit_softmax | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T05:34:19+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# {MODEL_NAME}
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 sentence-transformers installed:
Then you can u... | [
"# {MODEL_NAME}\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 you have sentence-transformers installed:\n\n\n\n... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# {MODEL_NAME}\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 se... |
token-classification | transformers | # ✨ vibert-capitalization-punctuation
This a [viBERT](https://huggingface.co/FPTAI/vibert-base-cased) model finetuned for punctuation restoration on the [OSCAR-2109](https://huggingface.co/datasets/oscar-corpus/OSCAR-2109) dataset.
The model predicts the punctuation and upper-casing of plain, lower-cased text. An exam... | {"language": ["vi"], "license": "cc-by-sa-4.0", "tags": ["capitalization", "punctuation", "token-classification"], "datasets": ["oscar-corpus/OSCAR-2109"], "metrics": ["accuracy", "precision", "recall", "f1"]} | dragonSwing/vibert-capu | null | [
"transformers",
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"bert",
"capitalization",
"punctuation",
"token-classification",
"vi",
"dataset:oscar-corpus/OSCAR-2109",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T05:45:40+00:00 | [] | [
"vi"
] | TAGS
#transformers #pytorch #bert #capitalization #punctuation #token-classification #vi #dataset-oscar-corpus/OSCAR-2109 #license-cc-by-sa-4.0 #endpoints_compatible #has_space #region-us
| vibert-capitalization-punctuation
=================================
This a viBERT model finetuned for punctuation restoration on the OSCAR-2109 dataset.
The model predicts the punctuation and upper-casing of plain, lower-cased text. An example use case can be ASR output. Or other cases when text has lost punctuation.... | [] | [
"TAGS\n#transformers #pytorch #bert #capitalization #punctuation #token-classification #vi #dataset-oscar-corpus/OSCAR-2109 #license-cc-by-sa-4.0 #endpoints_compatible #has_space #region-us \n"
] |
token-classification | transformers | # ✨ xlm-roberta-capitalization-punctuation
This a [XLM-RoBERTa](https://huggingface.co/xlm-roberta-base) model finetuned for Vietnamese punctuation restoration on the [OSCAR-2109](https://huggingface.co/datasets/oscar-corpus/OSCAR-2109) dataset.
The model predicts the punctuation and upper-casing of plain, lower-cased... | {"language": ["vi"], "license": "cc-by-sa-4.0", "tags": ["capitalization", "punctuation", "token-classification"], "datasets": ["oscar-corpus/OSCAR-2109"], "metrics": ["accuracy", "precision", "recall", "f1"]} | dragonSwing/xlm-roberta-capu | null | [
"transformers",
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"bert",
"capitalization",
"punctuation",
"token-classification",
"vi",
"dataset:oscar-corpus/OSCAR-2109",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T05:46:21+00:00 | [] | [
"vi"
] | TAGS
#transformers #pytorch #bert #capitalization #punctuation #token-classification #vi #dataset-oscar-corpus/OSCAR-2109 #license-cc-by-sa-4.0 #endpoints_compatible #has_space #region-us
| xlm-roberta-capitalization-punctuation
======================================
This a XLM-RoBERTa model finetuned for Vietnamese punctuation restoration on the OSCAR-2109 dataset.
The model predicts the punctuation and upper-casing of plain, lower-cased text. An example use case can be ASR output. Or other cases when ... | [] | [
"TAGS\n#transformers #pytorch #bert #capitalization #punctuation #token-classification #vi #dataset-oscar-corpus/OSCAR-2109 #license-cc-by-sa-4.0 #endpoints_compatible #has_space #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/1521957986335297536/itVS... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true", "widget": [{"text": "My dream is"}]} | huggingtweets/elonmusk-kimkardashian | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T06:03:46+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI CYBORG
Elon Musk & Kim Kardashian
@elonmusk-kimkardashian
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B repo... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
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... | wesleywt/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T06:26:41+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 |
# This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
## 1. Install PyTorch
```
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio==0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
```
## 2. Install Megatron
```
git clone http... | {"tags": ["opt_metasq"]} | patrickvonplaten/opt_metaseq_13000m | null | [
"opt_metasq",
"region:us"
] | null | 2022-05-11T06:40:12+00:00 | [] | [] | TAGS
#opt_metasq #region-us
|
# This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
## 1. Install PyTorch
## 2. Install Megatron
## 3. Install fairscale
## 4. Install metaseq
## 5. Clone this repo (click top right on "How to clone")
## 6. Run the following:
| [
"# This repo let's you run the following checkpoint using facebookresearch/metaseq.\n\nDo the following:",
"## 1. Install PyTorch",
"## 2. Install Megatron",
"## 3. Install fairscale",
"## 4. Install metaseq",
"## 5. Clone this repo (click top right on \"How to clone\")",
"## 6. Run the following:"
] | [
"TAGS\n#opt_metasq #region-us \n",
"# This repo let's you run the following checkpoint using facebookresearch/metaseq.\n\nDo the following:",
"## 1. Install PyTorch",
"## 2. Install Megatron",
"## 3. Install fairscale",
"## 4. Install metaseq",
"## 5. Clone this repo (click top right on \"How to clone\"... |
null | null |
# This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
## 1. Install PyTorch
```
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio==0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
```
## 2. Install Megatron
```
git clone http... | {"tags": ["opt_metasq"]} | patrickvonplaten/opt_metaseq_30000m | null | [
"opt_metasq",
"region:us"
] | null | 2022-05-11T06:40:41+00:00 | [] | [] | TAGS
#opt_metasq #region-us
|
# This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
## 1. Install PyTorch
## 2. Install Megatron
## 3. Install fairscale
## 4. Install metaseq
## 5. Clone this repo (click top right on "How to clone")
## 6. Run the following:
| [
"# This repo let's you run the following checkpoint using facebookresearch/metaseq.\n\nDo the following:",
"## 1. Install PyTorch",
"## 2. Install Megatron",
"## 3. Install fairscale",
"## 4. Install metaseq",
"## 5. Clone this repo (click top right on \"How to clone\")",
"## 6. Run the following:"
] | [
"TAGS\n#opt_metasq #region-us \n",
"# This repo let's you run the following checkpoint using facebookresearch/metaseq.\n\nDo the following:",
"## 1. Install PyTorch",
"## 2. Install Megatron",
"## 3. Install fairscale",
"## 4. Install metaseq",
"## 5. Clone this repo (click top right on \"How to clone\"... |
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... | ra-XOr/sphinx3-DQN | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T06:41:24+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... |
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. -->
# bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv
This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv]... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv", "results": []}]} | theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv | null | [
"transformers",
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T06:49:27+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv
========================================
This model is a fine-tuned version of theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8065
* Rouge1: 54.5916
* Rouge2: 36.7817
* Rougel: 40.4708... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-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: 5\n* mixed\\_precis... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size:... |
token-classification | transformers | Fine tuned recobo/agriculture-bert-uncased for custom NER entities. | {} | Wanjiru/ag_based_ner | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T06:51:14+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #token-classification #autotrain_compatible #endpoints_compatible #region-us
| Fine tuned recobo/agriculture-bert-uncased for custom NER entities. | [] | [
"TAGS\n#transformers #pytorch #bert #token-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
null | null | Helo
| {} | Sho/Sho_SRCNN | null | [
"region:us"
] | null | 2022-05-11T07:13:37+00:00 | [] | [] | TAGS
#region-us
| Helo
| [] | [
"TAGS\n#region-us \n"
] |
audio-classification | transformers |
# Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier
Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier is an audio classification model based on the [XLS-R](https://arxiv.org/abs/2111.09296) architecture. This model is a fine-tuned version of [wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-x... | {"language": "id", "license": "apache-2.0", "tags": ["audio-classification", "generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "wav2vec2-xls-r-adult-child-id-cls", "results": []}]} | bookbot/wav2vec2-xls-r-adult-child-id-cls | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"id",
"arxiv:2111.09296",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T07:13:39+00:00 | [
"2111.09296"
] | [
"id"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2111.09296 #license-apache-2.0 #endpoints_compatible #region-us
| Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier
=======================================================
Wav2Vec2 XLS-R Adult/Child Indonesian Speech Classifier is an audio classification model based on the XLS-R architecture. This model is a fine-tuned version of wav2vec2-xls-r-300m on a private adult/child I... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* 'learning\\_rate': 3e-05\n* 'train\\_batch\\_size': 8\n* 'eval\\_batch\\_size': 8\n* 'seed': 42\n* 'gradient\\_accumulation\\_steps': 4\n* 'total\\_train\\_batch\\_size': 32\n* 'optimizer': Adam with 'betas=(0.9,0.999... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2111.09296 #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': 3e-05\n* 'train\\... |
text-classification | transformers | # Erlangshen-MegatronBert-1.3B-Semtiment
- Github: [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)
- Docs: [Fengshenbang-Docs](https://fengshenbang-doc.readthedocs.io/)
## 简介 Brief Introduction
2021年登顶FewCLUE和ZeroCLUE的中文BERT，在数个情感分析任务微调后的版本
This is the fine-tuned version of the Chinese BERT model on... | {"language": ["zh"], "license": "apache-2.0", "tags": ["bert", "NLU", "Sentiment"], "inference": true, "widget": [{"text": "\u4eca\u5929\u5fc3\u60c5\u4e0d\u597d"}]} | IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Sentiment | null | [
"transformers",
"pytorch",
"megatron-bert",
"text-classification",
"bert",
"NLU",
"Sentiment",
"zh",
"arxiv:2209.02970",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T07:16:03+00:00 | [
"2209.02970"
] | [
"zh"
] | TAGS
#transformers #pytorch #megatron-bert #text-classification #bert #NLU #Sentiment #zh #arxiv-2209.02970 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| Erlangshen-MegatronBert-1.3B-Semtiment
======================================
* Github: Fengshenbang-LM
* Docs: Fengshenbang-Docs
简介 Brief Introduction
---------------------
2021年登顶FewCLUE和ZeroCLUE的中文BERT，在数个情感分析任务微调后的版本
This is the fine-tuned version of the Chinese BERT model on several sentiment analysis data... | [
"### 下游效果 Performance\n\n\n\n使用 Usage\n--------\n\n\n引用 Citation\n-----------\n\n\n如果您在您的工作中使用了我们的模型，可以引用我们的论文：\n\n\nIf you are using the resource for your work, please cite the our paper:\n\n\n也可以引用我们的网站:\n\n\nYou can also cite our website:"
] | [
"TAGS\n#transformers #pytorch #megatron-bert #text-classification #bert #NLU #Sentiment #zh #arxiv-2209.02970 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### 下游效果 Performance\n\n\n\n使用 Usage\n--------\n\n\n引用 Citation\n-----------\n\n\n如果您在您的工作中使用了我们的模型，可以引用我们的论文：\n... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | {"language": "en", "license": "other", "tags": ["text-generation", "opt"], "inference": false, "commercial": false} | facebook/opt-125m | null | [
"transformers",
"pytorch",
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"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:25:17+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Content... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing O... | {"language": "en", "license": "other", "tags": ["text-generation"], "inference": false, "commercial": false} | facebook/opt-350m | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:25:39+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Conten... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | {"language": "en", "license": "other", "tags": ["text-generation", "opt"], "inference": false, "commercial": false} | facebook/opt-1.3b | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:26:00+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Content... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | {"language": "en", "license": "other", "tags": ["text-generation", "opt"], "inference": false, "commercial": false} | facebook/opt-2.7b | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:26:30+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Content... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | {"language": "en", "license": "other", "tags": ["text-generation", "opt"], "inference": false, "commercial": false} | facebook/opt-6.7b | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:26:52+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Content... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | {"language": "en", "license": "other", "tags": ["opt", "text-generation"], "inference": false, "commercial": false} | facebook/opt-13b | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:27:07+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Content... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
text-generation | transformers |
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI.
**Disclaimer**: The team releasing OP... | {"language": "en", "license": "other", "tags": ["text-generation", "opt"], "inference": false, "commercial": false} | facebook/opt-30b | null | [
"transformers",
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"license:other",
"autotrain_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:27:14+00:00 | [
"2205.01068",
"2005.14165"
] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us
|
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.
Disclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper.
Content... | [
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language Models and first released in metaseq's repository on May 3rd 2022 by Meta AI.\n\nDisclaimer: The team releasing OPT wrote an official model card, which is available in Appendix D of the paper. ... | [
"TAGS\n#transformers #pytorch #tf #jax #opt #text-generation #en #arxiv-2205.01068 #arxiv-2005.14165 #license-other #autotrain_compatible #has_space #text-generation-inference #region-us \n",
"# OPT : Open Pre-trained Transformer Language Models\n\nOPT was first introduced in Open Pre-trained Transformer Language... |
feature-extraction | transformers |
# This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
## 1. Install PyTorch
```
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio==0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
```
## 2. Install Megatron
```
git clone http... | {"tags": ["opt_metasq"]} | patrickvonplaten/opt_metaseq_350m | null | [
"transformers",
"opt",
"feature-extraction",
"opt_metasq",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T07:35:10+00:00 | [] | [] | TAGS
#transformers #opt #feature-extraction #opt_metasq #endpoints_compatible #text-generation-inference #region-us
|
# This repo let's you run the following checkpoint using facebookresearch/metaseq.
Do the following:
## 1. Install PyTorch
## 2. Install Megatron
## 3. Install fairscale
## 4. Install metaseq
## 5. Clone this repo (click top right on "How to clone")
## 6. Run the following:
| [
"# This repo let's you run the following checkpoint using facebookresearch/metaseq.\n\nDo the following:",
"## 1. Install PyTorch",
"## 2. Install Megatron",
"## 3. Install fairscale",
"## 4. Install metaseq",
"## 5. Clone this repo (click top right on \"How to clone\")",
"## 6. Run the following:"
] | [
"TAGS\n#transformers #opt #feature-extraction #opt_metasq #endpoints_compatible #text-generation-inference #region-us \n",
"# This repo let's you run the following checkpoint using facebookresearch/metaseq.\n\nDo the following:",
"## 1. Install PyTorch",
"## 2. Install Megatron",
"## 3. Install fairscale",
... |
null | null | Fixed parameters:
* **model_name_or_path**: `Bhumika/roberta-base-finetuned-sst2`
* **dataset**:
* **path**: `glue`
* **name**: `sst2`
* **calibration_split**: `None`
* **eval_split**: `validation`
* **data_keys**: `['sentence']`
* **label_keys**: `['label']`
* **quantization_approach**: `dynami... | {} | fxmarty/donotdelete | null | [
"region:us"
] | null | 2022-05-11T07:51:40+00:00 | [] | [] | TAGS
#region-us
| Fixed parameters:
* model_name_or_path: 'Bhumika/roberta-base-finetuned-sst2'
* dataset:
* path: 'glue'
* name: 'sst2'
* calibration_split: 'None'
* eval_split: 'validation'
* data_keys: '['sentence']'
* label_keys: '['label']'
* quantization_approach: 'dynamic'
* node_exclusion: '[]'
* per_chan... | [
"## Evaluation\nBelow, time metrics for\n* Batch size: 8\n* Input length: 128\n| operators_to_quantize | | latency_mean (original, ms) | latency_mean (optimized, ms) | | throughput (original, /s) | throughput (optimized, /s) | | accuracy (original) | accuracy (optimized) |\n| :-------------------: | :-:... | [
"TAGS\n#region-us \n",
"## Evaluation\nBelow, time metrics for\n* Batch size: 8\n* Input length: 128\n| operators_to_quantize | | latency_mean (original, ms) | latency_mean (optimized, ms) | | throughput (original, /s) | throughput (optimized, /s) | | accuracy (original) | accuracy (optimized) |\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/1424546909104926720/g4pT... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/alice_lbl-lotrbookquotes-theprincess_lbl/1652500340141/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/alice_lbl-lotrbookquotes-theprincess_lbl | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T08:16:14+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI CYBORG
Alice in Wonderland & Looking-Glass (line by line) & Lord of the Rings quotes & The Princess Bride (line by line)
@alice\_lbl-lotrbookquotes-theprincess\_lbl
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model ... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text2text-generation | transformers |
IndicBART-XLSum is a multilingual separate script [IndicBART](https://huggingface.co/ai4bharat/IndicBARTSS) based, sequence-to-sequence pre-trained model focusing on Indic languages. It currently supports 7 Indian languages and is based on the mBART architecture. Some salient features of the IndicBART-XLSum are:
<ul... | {"language": ["bn", "gu", "hi", "mr", "pa", "ta", "te"], "tags": ["multilingual", "nlp", "indicnlp"], "datasets": ["csebuetnlp/xlsum"], "widget": ["\u091f\u0947\u0938\u093e \u091c\u0949\u0935\u0932 \u0915\u093e \u0915\u0939\u0928\u093e \u0939\u0948 \u0915\u093f \u092e\u0943\u0924\u0915\u094b\u0902 \u0914\u0930 \u0932\u... | ai4bharat/IndicBART-XLSum | null | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"multilingual",
"nlp",
"indicnlp",
"bn",
"gu",
"hi",
"mr",
"pa",
"ta",
"te",
"dataset:csebuetnlp/xlsum",
"arxiv:2109.02903",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-05-11T08:24:38+00:00 | [
"2109.02903"
] | [
"bn",
"gu",
"hi",
"mr",
"pa",
"ta",
"te"
] | TAGS
#transformers #pytorch #mbart #text2text-generation #multilingual #nlp #indicnlp #bn #gu #hi #mr #pa #ta #te #dataset-csebuetnlp/xlsum #arxiv-2109.02903 #autotrain_compatible #endpoints_compatible #has_space #region-us
| IndicBART-XLSum is a multilingual separate script IndicBART based, sequence-to-sequence pre-trained model focusing on Indic languages. It currently supports 7 Indian languages and is based on the mBART architecture. Some salient features of the IndicBART-XLSum are:
* Supported languages: Bengali, Gujarati, Hindi, Mar... | [] | [
"TAGS\n#transformers #pytorch #mbart #text2text-generation #multilingual #nlp #indicnlp #bn #gu #hi #mr #pa #ta #te #dataset-csebuetnlp/xlsum #arxiv-2109.02903 #autotrain_compatible #endpoints_compatible #has_space #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... | muks/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T08:30:55+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 |
# POET: A French Extended Part-of-Speech Tagger
- Corpora: [ANTILLES](https://github.com/qanastek/ANTILLES)
- Embeddings & Sequence Labelling: [CamemBERT](https://arxiv.org/abs/1911.03894)
- Number of Epochs: 115
**People Involved**
* [LABRAK Yanis](https://www.linkedin.com/in/yanis-labrak-8a7412145/) (1)
* [DUFOUR... | {"language": "fr", "tags": ["Transformers", "token-classification", "sequence-tagger-model"], "datasets": ["qanastek/ANTILLES"], "widget": [{"text": "George Washington est all\u00e9 \u00e0 Washington"}]} | taln-ls2n/POET | null | [
"transformers",
"pytorch",
"camembert",
"token-classification",
"Transformers",
"sequence-tagger-model",
"fr",
"dataset:qanastek/ANTILLES",
"arxiv:1911.03894",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T08:33:05+00:00 | [
"1911.03894"
] | [
"fr"
] | TAGS
#transformers #pytorch #camembert #token-classification #Transformers #sequence-tagger-model #fr #dataset-qanastek/ANTILLES #arxiv-1911.03894 #autotrain_compatible #endpoints_compatible #region-us
| POET: A French Extended Part-of-Speech Tagger
=============================================
* Corpora: ANTILLES
* Embeddings & Sequence Labelling: CamemBERT
* Number of Epochs: 115
People Involved
* LABRAK Yanis (1)
* DUFOUR Richard (2)
Affiliations
1. LIA, NLP team, Avignon University, Avignon, France.
2. LS... | [] | [
"TAGS\n#transformers #pytorch #camembert #token-classification #Transformers #sequence-tagger-model #fr #dataset-qanastek/ANTILLES #arxiv-1911.03894 #autotrain_compatible #endpoints_compatible #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. -->
# distilbert-poem_key_words
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilbert-poem_key_words", "results": []}]} | guhuawuli/distilbert-poem_key_words | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T08:35:17+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbert-poem\_key\_words
===========================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation dat... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-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: 5e-05\n* train\\_b... |
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)
Using this model becomes easy when you have stable-baselines3 and huggingface_... | {"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... | kingabzpro/Moonman-Lunar-Landing-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T08:44:34+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)
Using this model becomes easy when you have stable-baselines3 and huggingface_sb3 installed:
Then, you can use the model like this:
| [
"# 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\nUsing this model becomes easy when you have stable-baselines3 and huggingface_sb3 installed:\n\nThen, you can use the model like this:... | [
"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\nUsing th... |
text-generation | transformers |
# DistilGPT2-Beatles-Lyrics-finetuned
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the [Huggingartists - beatles](https://huggingface.co/datasets/huggingartists/the-beatles) dataset. It will complete an input prompt with Beatles-like text.
### Training hyperparameters
Th... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "widget": [{"text": "Last night in Kiev the", "example_title": "Kiev"}, {"text": "It hasn't rained in weeks", "example_title": "Rain"}], "model-index": [{"name": "DistilGPT2-Beatles-Lyrics-finetuned", "results": []}]} | wvangils/DistilGPT2-Beatles-Lyrics-finetuned | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-05-11T08:51:46+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| DistilGPT2-Beatles-Lyrics-finetuned
===================================
This model is a fine-tuned version of distilgpt2 on the Huggingartists - beatles dataset. It will complete an input prompt with Beatles-like text.
### Training hyperparameters
The following hyperparameters were used during training:
* learn... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 4\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 #gpt2 #text-generation #generated_from_trainer #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* learning\\_rate: 5... |
audio-classification | transformers |
# Wav2Vec2 Adult/Child Indonesian Speech Classifier
Wav2Vec2 Adult/Child Indonesian Speech Classifier is an audio classification model based on the [wav2vec 2.0](https://arxiv.org/abs/2006.11477) architecture. This model is a fine-tuned version of [wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on a pr... | {"language": "id", "license": "apache-2.0", "tags": ["audio-classification", "generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "wav2vec2-adult-child-id-cls", "results": []}]} | bookbot/wav2vec2-adult-child-id-cls | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"id",
"arxiv:2006.11477",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T09:06:43+00:00 | [
"2006.11477"
] | [
"id"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2006.11477 #license-apache-2.0 #endpoints_compatible #region-us
| Wav2Vec2 Adult/Child Indonesian Speech Classifier
=================================================
Wav2Vec2 Adult/Child Indonesian Speech Classifier is an audio classification model based on the wav2vec 2.0 architecture. This model is a fine-tuned version of wav2vec2-base on a private adult/child Indonesian speech c... | [
"### 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* 'optimizer': Adam with 'betas=(0.9,0.999)' and 'epsilon=1e-08'\n* 'lr\\_scheduler\\_type': linear\n* 'lr\\_scheduler... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #id #arxiv-2006.11477 #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': 3e-05\n* 'train\\... |
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... | ankkarp/ppo-LunarLander-v2_v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T09:14:35+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... |
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... | alexmelekhin/TEST-ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T09:31:07+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
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... | QuickSilver007/rlunit1_ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T09:32:19+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... | mustapha/Lunar_lander_v2_gym_2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T09:36:28+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... |
automatic-speech-recognition | speechbrain |
| Release | Test WER | GPUs |
|:-------------:|:--------------:| :--------:|
| 22-05-11 | - | 1xK80 24GB |
after 9 epochs training - valid %WER: 4.09e+02
after 12 epochs training - valid %WER: 2.07e+02, test WER: 1.78e+02
## Pipeline description
(by SpeechBrain text)
This ASR system is composed with 3 different bu... | {"language": "ru", "license": "apache-2.0", "tags": ["automatic-speech-recognition", "CTC", "Attention", "pytorch", "speechbrain"], "datasets": ["buriy-audiobooks-2-val"], "metrics": ["wer", "cer"]} | AndyGo/speechbrain-asr-crdnn-rnnlm-buriy-audiobooks-2-val | null | [
"speechbrain",
"automatic-speech-recognition",
"CTC",
"Attention",
"pytorch",
"ru",
"dataset:buriy-audiobooks-2-val",
"arxiv:2106.04624",
"license:apache-2.0",
"region:us"
] | null | 2022-05-11T10:08:46+00:00 | [
"2106.04624"
] | [
"ru"
] | TAGS
#speechbrain #automatic-speech-recognition #CTC #Attention #pytorch #ru #dataset-buriy-audiobooks-2-val #arxiv-2106.04624 #license-apache-2.0 #region-us
|
after 9 epochs training - valid %WER: 4.09e+02
after 12 epochs training - valid %WER: 2.07e+02, test WER: 1.78e+02
Pipeline description
--------------------
(by SpeechBrain text)
This ASR system is composed with 3 different but linked blocks:
* Tokenizer (unigram) that transforms words into subword units and t... | [
"### Transcribing your own audio files (in Russian)",
"### Inference on GPU\n\n\nTo perform inference on the GPU, add 'run\\_opts={\"device\":\"cuda\"}' when calling the 'from\\_hparams' method.",
"### Russian Speech Datasets\n\n\nRussian Speech Datasets are provided by Microsoft Corporation with CC BY-NC licen... | [
"TAGS\n#speechbrain #automatic-speech-recognition #CTC #Attention #pytorch #ru #dataset-buriy-audiobooks-2-val #arxiv-2106.04624 #license-apache-2.0 #region-us \n",
"### Transcribing your own audio files (in Russian)",
"### Inference on GPU\n\n\nTo perform inference on the GPU, add 'run\\_opts={\"device\":\"cud... |
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... | crow/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T10:12:20+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\n This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.\n \n ## Usage (with Stable-baselines3)\n TODO: Ad... |
image-classification | transformers |
# beer-whisky-wine-detection
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/n... | {"tags": ["image-classification", "pytorch", "huggingpics"], "metrics": ["accuracy"]} | firas-spanioli/beer-whisky-wine-detection | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T10:38:29+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# beer-whisky-wine-detection
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
#### beer
!beer
#### whisky
!whisky
#### wine
!wine | [
"# beer-whisky-wine-detection\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",
"#### beer\n\n!beer",
"#### whisky\n\n!whisky",
"#### wine\n\n!wine"
] | [
"TAGS\n#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# beer-whisky-wine-detection\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nRepo... |
image-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. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["image_folder"], "metrics": ["accuracy"], "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-eurosat", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "image_folder", "type... | guhuawuli/swin-tiny-patch4-window7-224-finetuned-eurosat | null | [
"transformers",
"pytorch",
"tensorboard",
"swin",
"image-classification",
"generated_from_trainer",
"dataset:image_folder",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T11:29:27+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #dataset-image_folder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| swin-tiny-patch4-window7-224-finetuned-eurosat
==============================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the image\_folder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0977
* Accuracy: 0.9678
Model description
----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 128\n* eval\\_batch\\_size: 128\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 512\n* optimizer: Adam with betas=(0.9,0.999) and epsi... | [
"TAGS\n#transformers #pytorch #tensorboard #swin #image-classification #generated_from_trainer #dataset-image_folder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
sentence-similarity | sentence-transformers |
# Style Embedding
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.
for more info see [Style-Embeddings](https://github.com/nlpsoc/Style-Embeddings)
## Usage (Sentence-T... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | AnnaWegmann/Style-Embedding | null | [
"sentence-transformers",
"pytorch",
"roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T11:42:35+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #roberta #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# Style Embedding
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.
for more info see Style-Embeddings
## Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-tran... | [
"# Style Embedding\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.\n\nfor more info see Style-Embeddings",
"## Usage (Sentence-Transformers)\n\nUsing this model becomes easy when you have... | [
"TAGS\n#sentence-transformers #pytorch #roberta #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# Style Embedding\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... |
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. -->
# finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED
This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED", "results": []}]} | lucaordronneau/finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T11:45:07+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
| finbert-finetuned-FG-SINGLE\_SENTENCE-NEWS-WEIGHTED
===================================================
This model is a fine-tuned version of ProsusAI/finbert on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.2741
* Accuracy: 0.7475
* F1: 0.7253
Model description
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 6e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 16",
"### Train... | [
"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: 6e-05\n* train\\_batch\\_size: 48\n* eval\\_... |
sentence-similarity | sentence-transformers |
# {MODEL_NAME}
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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
Using this model becomes easy when ... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | ceggian/sbert_pt_reddit_mnr_512 | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T12:18:47+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# {MODEL_NAME}
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 sentence-transformers installed:
Then you can u... | [
"# {MODEL_NAME}\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 you have sentence-transformers installed:\n\n\n\n... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# {MODEL_NAME}\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 se... |
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... | redshift51/ab_LunarLander-v2_1 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-05-11T12:19:49+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 the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hi-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": "hi-TAPT-MLM-MiniLM", "results": []}]} | subhasisj/hi-TAPT-MLM-MiniLM | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T12:30:08+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
|
# hi-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... | [
"# hi-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",
"# hi-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",... |
sentence-similarity | sentence-transformers |
# orenpereg/paraphrase-mpnet-base-v2_sst2_4samps
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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
U... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | orenpereg/paraphrase-mpnet-base-v2_sst2_4samps | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T12:32:16+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# orenpereg/paraphrase-mpnet-base-v2_sst2_4samps
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 sentence-transfo... | [
"# orenpereg/paraphrase-mpnet-base-v2_sst2_4samps\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 you have senten... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# orenpereg/paraphrase-mpnet-base-v2_sst2_4samps\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be u... |
sentence-similarity | sentence-transformers |
# orenpereg/paraphrase-mpnet-base-v2_sst2_64samps
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.
<!--- Describe your model here -->
## Usage (Sentence-Transformers)
... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | orenpereg/paraphrase-mpnet-base-v2_sst2_64samps | null | [
"sentence-transformers",
"pytorch",
"mpnet",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-05-11T12:40:24+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# orenpereg/paraphrase-mpnet-base-v2_sst2_64samps
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 sentence-transf... | [
"# orenpereg/paraphrase-mpnet-base-v2_sst2_64samps\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 you have sente... | [
"TAGS\n#sentence-transformers #pytorch #mpnet #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# orenpereg/paraphrase-mpnet-base-v2_sst2_64samps\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be ... |
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