pipeline_tag stringclasses 48
values | library_name stringclasses 198
values | text stringlengths 1 900k | metadata stringlengths 2 438k | id stringlengths 5 122 | last_modified null | tags listlengths 1 1.84k | sha null | created_at stringlengths 25 25 | arxiv listlengths 0 201 | languages listlengths 0 1.83k | tags_str stringlengths 17 9.34k | text_str stringlengths 0 389k | text_lists listlengths 0 722 | processed_texts listlengths 1 723 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech-sat_s42
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_unispeech-sat_s42 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:08:25+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech-sat_s42
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_unispeech-sat_s42\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech-sat_s42\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_xls-r_s118
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_xls-r_s118 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:12:22+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_xls-r_s118
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_xls-r_s118\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_xls-r_s118\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (e... |
text-classification | 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. -->
# europython-imdb
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on... | {"license": "mit", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "europython-imdb", "results": []}]} | jstrnad/europython-imdb | null | [
"transformers",
"tf",
"deberta-v2",
"text-classification",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:13:48+00:00 | [] | [] | TAGS
#transformers #tf #deberta-v2 #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us
| europython-imdb
===============
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 0.1802
* Train Accuracy: 0.9293
* Validation Loss: 0.2424
* Validation Accuracy: 0.9115
* Epoch: 1
Model description
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 2e-05, 'decay': 0.0, 'beta\\_1': 0.9, 'beta\\_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}\n* training\\_precision: float32",
"### Training results",
"### Framework... | [
"TAGS\n#transformers #tf #deberta-v2 #text-classification #generated_from_keras_callback #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'learning\\_rate': 2e-05,... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_xls-r_s691
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_xls-r_s691 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:18:30+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_xls-r_s691
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_xls-r_s691\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_xls-r_s691\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (e... |
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. -->
# recipe-roberta-tis
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-roberta-tis", "results": []}]} | paola-md/recipe-roberta-tis | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:22:05+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| recipe-roberta-tis
==================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8491
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More infor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 256\n* eval\\_batch\\_size: 256\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20\n* mixed\\_p... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #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\\_size: 256\n* eval\\_batch\... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_xls-r_s51
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_xls-r_s51 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:22:32+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_xls-r_s51
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_xls-r_s51\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_xls-r_s51\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (es... |
reinforcement-learning | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
| {"tags": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-CartPole", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{"ty... | AdiKompella/Reinforce-CartPole | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2022-07-11T15:25:53+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL"
] | [
"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcemen... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_r-wav2vec2_s809
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_r-wav2vec2_s809 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:26:08+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_r-wav2vec2_s809
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_r-wav2vec2_s809\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_r-wav2vec2_s809\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-small-spanish-historias-conflicto-colpoetry-historias-conflicto-col
This model is a fine-tuned version of [jorge-henao/gpt2... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "gpt2-small-spanish-historias-conflicto-colpoetry-historias-conflicto-col", "results": []}]} | jorge-henao/gpt2-small-spanish-historias-conflicto-colpoetry-historias-conflicto-col | null | [
"transformers",
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T15:29:51+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
|
# gpt2-small-spanish-historias-conflicto-colpoetry-historias-conflicto-col
This model is a fine-tuned version of jorge-henao/gpt2-small-spanish-historias-conflicto-col on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5017
## Model description
More information needed
## In... | [
"# gpt2-small-spanish-historias-conflicto-colpoetry-historias-conflicto-col\n\nThis model is a fine-tuned version of jorge-henao/gpt2-small-spanish-historias-conflicto-col on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 4.5017",
"## Model description\n\nMore information n... | [
"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",
"# gpt2-small-spanish-historias-conflicto-colpoetry-historias-conflicto-col\n\nThis model is a fine-tuned version of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_r-wav2vec2_s870
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_r-wav2vec2_s870 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:29:58+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_r-wav2vec2_s870
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_r-wav2vec2_s870\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_r-wav2vec2_s870\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
reinforcement-learning | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
| {"tags": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "reinforce-CartPole-v1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{... | ianspektor/reinforce-CartPole-v1 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2022-07-11T15:33:35+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL"
] | [
"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcemen... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_r-wav2vec2_s227
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_r-wav2vec2_s227 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:33:36+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_r-wav2vec2_s227
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_r-wav2vec2_s227\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_r-wav2vec2_s227\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comple... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | alefarasin/testpyramidsrnd | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2022-07-11T15:37:35+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the trainin... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the t... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documen... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-it_s438
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-it_s438 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:40:28+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_vp-it_s438
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_vp-it_s438\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_vp-it_s438\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-it_s179
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-it_s179 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:44:09+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_vp-it_s179
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_vp-it_s179\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_vp-it_s179\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
token-classification | transformers | # tner/twitter-roberta-base-dec2021-tweetner7-random
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-dec2021](https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2021) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_random` split).
Model fine-tuning... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/twitter-roberta-base-dec2021-tweetner7-random | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:45:35+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/twitter-roberta-base-dec2021-tweetner7-random
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2021 on the
tner/tweetner7 dataset ('train_random' split).
Model fine-tuning is done via T-NER's hyper-parameter search (see the repository
for more detail). It achieves the following results ... | [
"# tner/twitter-roberta-base-dec2021-tweetner7-random\n\nThis model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2021 on the \ntner/tweetner7 dataset ('train_random' split).\nModel fine-tuning is done via T-NER's hyper-parameter search (see the repository\nfor more detail). It achieves the followin... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/twitter-roberta-base-dec2021-tweetner7-random\n\nThis model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2021 on the \ntner/tweetne... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-it_s320
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-it_s320 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:47:38+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_vp-it_s320
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (es).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_es_vp-it_s320\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (es).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_vp-it_s320\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_wav2vec2_s250
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_wav2vec2_s250 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:51:14+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_wav2vec2_s250
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_wav2vec2_s250\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_wav2vec2_s250\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_wav2vec2_s515
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_wav2vec2_s515 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:54:22+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_wav2vec2_s515
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_wav2vec2_s515\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_wav2vec2_s515\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_wav2vec2_s859
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_wav2vec2_s859 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:57:41+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_wav2vec2_s859
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_wav2vec2_s859\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_wav2vec2_s859\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition using the train split of Common Voice 7.0... |
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. -->
# xlm-roberta-base-squad-pt
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on t... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad_v1_pt"], "model-index": [{"name": "xlm-roberta-base-squad-pt", "results": []}]} | ArthurBaia/xlm-roberta-base-squad-pt | null | [
"transformers",
"pytorch",
"xlm-roberta",
"question-answering",
"generated_from_trainer",
"dataset:squad_v1_pt",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:59:16+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #question-answering #generated_from_trainer #dataset-squad_v1_pt #license-mit #endpoints_compatible #region-us
|
# xlm-roberta-base-squad-pt
This model is a fine-tuned version of xlm-roberta-base on the squad_v1_pt dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperp... | [
"# xlm-roberta-base-squad-pt\n\nThis model is a fine-tuned version of xlm-roberta-base on the squad_v1_pt dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training proc... | [
"TAGS\n#transformers #pytorch #xlm-roberta #question-answering #generated_from_trainer #dataset-squad_v1_pt #license-mit #endpoints_compatible #region-us \n",
"# xlm-roberta-base-squad-pt\n\nThis model is a fine-tuned version of xlm-roberta-base on the squad_v1_pt dataset.",
"## Model description\n\nMore inform... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-100k_s645
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-100k_s645 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:01:35+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-100k_s645
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-100k_s645\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-100k_s645\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
text-classification | transformers |
This model was trained with the [Rankers Library](`https://github.com/davidmrau/rankers`) please check https://github.com/davidmrau/rankers#Evaluation to learn how to use the model.
This Cross Encoder Ranking Model is invariant to the input order by removing the position embeddings (by being set to zero) during fin... | {"license": "afl-3.0"} | dmrau/bow-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:08:29+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #license-afl-3.0 #autotrain_compatible #endpoints_compatible #region-us
|
This model was trained with the Rankers Library please check URL to learn how to use the model.
This Cross Encoder Ranking Model is invariant to the input order by removing the position embeddings (by being set to zero) during fine-tuning. It was trained on the official MS MARCO training triples using the following... | [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #license-afl-3.0 #autotrain_compatible #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-100k_s660
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-100k_s660 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:09:38+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-100k_s660
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-100k_s660\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-100k_s660\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-100k_s69
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure th... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-100k_s69 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:13:17+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-100k_s69
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-100k_s69\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-100k_s69\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_xlsr-53_s677
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_xlsr-53_s677 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:16:33+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_xlsr-53_s677
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_xlsr-53_s677\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_xlsr-53_s677\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | tj-solergibert/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:19:16+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2158
* Accuracy: 0.9285
* F1: 0.9286
Model description
-----------------
Mo... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_xlsr-53_s454
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_xlsr-53_s454 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:19:49+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_xlsr-53_s454
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_xlsr-53_s454\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_xlsr-53_s454\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_xlsr-53_s829
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_xlsr-53_s829 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:23:00+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_xlsr-53_s829
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_xlsr-53_s829\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_xlsr-53_s829\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech_s186
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech_s186 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:26:14+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech_s186
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech_s186\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech_s186\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech_s474
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech_s474 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:29:33+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech_s474
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech_s474\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech_s474\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech_s952
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech_s952 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:32:54+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech_s952
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech_s952\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech_s952\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_hubert_s807
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_hubert_s807 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:36:06+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_hubert_s807
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_hubert_s807\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_hubert_s807\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt)... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_hubert_s301
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_hubert_s301 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:39:41+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_hubert_s301
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_hubert_s301\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_hubert_s301\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt)... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_hubert_s486
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_hubert_s486 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:42:50+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_hubert_s486
Fine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_hubert_s486\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #hubert #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_hubert_s486\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (pt)... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-sv_s612
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-sv_s612 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:47:09+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-sv_s612
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-sv_s612\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-sv_s612\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Pixelcopter-PLE-v0", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelco... | AdiKompella/Reinforce-Pixelcopter-PLE-v0 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2022-07-11T16:47:44+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL
| [
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL"
] | [
"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 5 of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-sv_s563
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-sv_s563 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:50:36+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-sv_s563
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-sv_s563\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-sv_s563\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
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. -->
# t5-small-finetuned-emo20q
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "t5-small-finetuned-emo20q", "results": []}]} | abecode/t5-small-finetuned-emo20q | null | [
"transformers",
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T16:52:23+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| t5-small-finetuned-emo20q
=========================
This model is a fine-tuned version of t5-small on the None dataset.
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
-------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1\n* mixed\\_prec... | [
"TAGS\n#transformers #pytorch #tensorboard #t5 #text2text-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... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-sv_s894
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-sv_s894 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:54:09+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-sv_s894
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-sv_s894\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-sv_s894\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_no-pretraining_s84
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has bee... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_no-pretraining_s84 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:57:34+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_no-pretraining_s84
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_no-pretraining_s84\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_no-pretraining_s84\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Comm... |
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. -->
# longformer-base-4096-finetuned-cola
This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/... | {"tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model-index": [{"name": "longformer-base-4096-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "args": "cola"}, "metrics": [{"... | alanwang8/default-longformer-base-4096-finetuned-cola | null | [
"transformers",
"pytorch",
"longformer",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T16:58:47+00:00 | [] | [] | TAGS
#transformers #pytorch #longformer #text-classification #generated_from_trainer #dataset-glue #model-index #autotrain_compatible #endpoints_compatible #region-us
| longformer-base-4096-finetuned-cola
===================================
This model is a fine-tuned version of allenai/longformer-base-4096 on the glue dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7005
* Matthews Correlation: 0.0
Model description
-----------------
More information... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 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* num\\_epochs: 5",
"### Traini... | [
"TAGS\n#transformers #pytorch #longformer #text-classification #generated_from_trainer #dataset-glue #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_no-pretraining_s541
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has be... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_no-pretraining_s541 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:01:02+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_no-pretraining_s541
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_no-pretraining_s541\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_no-pretraining_s541\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Com... |
token-classification | transformers | # 🤗 bert-restore-punctuation-ptbr
* 🪄 [W&B Dashboard](https://wandb.ai/dominguesm/RestorePunctuationPTBR)
* ⛭ [GitHub](https://github.com/DominguesM/respunct)
This is a [bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) model finetuned for punctuation restoration on [WikiLi... | {"language": ["pt"], "license": "cc-by-4.0", "tags": ["named-entity-recognition", "Transformer", "pytorch", "bert"], "datasets": ["wiki_lingua"], "metrics": ["f1", "precision", "recall"], "widget": [{"text": "henrique foi no lago pescar com o pedro mais tarde foram para a casa do pedro fritar os peixes"}, {"text": "cin... | dominguesm/bert-restore-punctuation-ptbr | null | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"Transformer",
"pt",
"dataset:wiki_lingua",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:04:21+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #safetensors #bert #token-classification #named-entity-recognition #Transformer #pt #dataset-wiki_lingua #license-cc-by-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| bert-restore-punctuation-ptbr
=============================
* W&B Dashboard
* GitHub
This is a bert-base-portuguese-cased model finetuned for punctuation restoration on WikiLingua.
This model is intended for direct use as a punctuation restoration model for the general Portuguese language. Alternatively, you can ... | [] | [
"TAGS\n#transformers #pytorch #safetensors #bert #token-classification #named-entity-recognition #Transformer #pt #dataset-wiki_lingua #license-cc-by-4.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_no-pretraining_s34
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has bee... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_no-pretraining_s34 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:05:36+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_no-pretraining_s34
Fine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_no-pretraining_s34\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_no-pretraining_s34\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Comm... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_wavlm_s51
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at 1... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_wavlm_s51 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:09:52+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_wavlm_s51
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_wavlm_s51\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wavlm #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_wavlm_s51\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen u... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_wavlm_s691
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at ... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_wavlm_s691 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:13:02+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_wavlm_s691
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_wavlm_s691\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wavlm #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_wavlm_s691\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen ... |
text-generation | transformers |
# Chatbot Stacey
Made for **LGBTQ+ Spacey**'s Bot on [Discord](https://discord.com/invite/jt4PWme44X).
[](https://github.com/ashtrindade/spacey-website-articles-api/blob/main/LICENSE.md)
---
## License
MIT License
Copyright (c) 2022 Ash Trindade
Perm... | {"tags": ["conversational"]} | ashtrindade/chatbot-stacey | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T17:20:24+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Chatbot Stacey
Made for LGBTQ+ Spacey's Bot on Discord.
 2022 Ash Trindade
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without r... | [
"# Chatbot Stacey\nMade for LGBTQ+ Spacey's Bot on Discord.\n![MIT License](URL\n\n---",
"## License\nMIT License\n\nCopyright (c) 2022 Ash Trindade\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in th... | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Chatbot Stacey\nMade for LGBTQ+ Spacey's Bot on Discord.\n![MIT License](URL\n\n---",
"## License\nMIT License\n\nCopyright (c) 2022 Ash Trindade\n\nPerm... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_wavlm_s118
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled at ... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_wavlm_s118 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:22:59+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_wavlm_s118
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_wavlm_s118\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wavlm #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_wavlm_s118\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen ... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech-ml_s324
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech-ml_s324 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:26:59+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech-ml_s324
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech-ml_s324\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech-ml_s324\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech-ml_s808
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech-ml_s808 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:30:46+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech-ml_s808
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech-ml_s808\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech-ml_s808\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | quanxi/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T17:32:11+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-tra... | [
"TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech-ml_s610
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech-ml_s610 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:44:41+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech-ml_s610
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech-ml_s610\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech-ml_s610\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-fr_s675
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-fr_s675 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:48:25+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-fr_s675
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-fr_s675\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-fr_s675\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
token-classification | transformers | # tner/twitter-roberta-base-dec2020-tweetner7-random
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-dec2020](https://huggingface.co/cardiffnlp/twitter-roberta-base-dec2020) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_random` split).
Model fine-tuning... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/twitter-roberta-base-dec2020-tweetner7-random | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:48:44+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/twitter-roberta-base-dec2020-tweetner7-random
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2020 on the
tner/tweetner7 dataset ('train_random' split).
Model fine-tuning is done via T-NER's hyper-parameter search (see the repository
for more detail). It achieves the following results ... | [
"# tner/twitter-roberta-base-dec2020-tweetner7-random\n\nThis model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2020 on the \ntner/tweetner7 dataset ('train_random' split).\nModel fine-tuning is done via T-NER's hyper-parameter search (see the repository\nfor more detail). It achieves the followin... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/twitter-roberta-base-dec2020-tweetner7-random\n\nThis model is a fine-tuned version of cardiffnlp/twitter-roberta-base-dec2020 on the \ntner/tweetne... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-fr_s485
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-fr_s485 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:53:30+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-fr_s485
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-fr_s485\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-fr_s485\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-fr_s752
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-fr_s752 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T17:57:25+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-fr_s752
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-fr_s752\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-fr_s752\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-es_s454
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-es_s454 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:01:28+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-es_s454
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-es_s454\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-es_s454\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-es_s506
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-es_s506 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:04:54+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-es_s506
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-es_s506\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-es_s506\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-es_s291
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-es_s291 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:08:58+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-es_s291
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-es_s291\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-es_s291\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-nl_s833
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-nl_s833 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:12:53+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-nl_s833
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-nl_s833\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-nl_s833\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-nl_s6
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-nl_s6 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:16:53+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-nl_s6
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-nl_s6\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-nl_s6\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice ... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-nl_s783
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-nl_s783 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:23:20+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-nl_s783
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-nl_s783\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-nl_s783\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech-sat_s756
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech-sat_s756 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:26:24+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech-sat_s756
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech-sat_s756\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech-sat_s756\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech-sat_s377
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech-sat_s377 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:29:59+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech-sat_s377
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech-sat_s377\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech-sat_s377\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_unispeech-sat_s103
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_unispeech-sat_s103 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:33:36+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_unispeech-sat_s103
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_unispeech-sat_s103\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #unispeech-sat #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_unispeech-sat_s103\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_xls-r_s17
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input i... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_xls-r_s17 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:37:21+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_xls-r_s17
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_xls-r_s17\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_xls-r_s17\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_xls-r_s689
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_xls-r_s689 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:40:50+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_xls-r_s689
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_xls-r_s689\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_xls-r_s689\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (p... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_xls-r_s657
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_xls-r_s657 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:44:32+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_xls-r_s657
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_xls-r_s657\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_xls-r_s657\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (p... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_r-wav2vec2_s468
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_r-wav2vec2_s468 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:47:54+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_r-wav2vec2_s468
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_r-wav2vec2_s468\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_r-wav2vec2_s468\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_r-wav2vec2_s957
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_r-wav2vec2_s957 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:51:07+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_r-wav2vec2_s957
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_r-wav2vec2_s957\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_r-wav2vec2_s957\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
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. -->
# recipe-roberta-upper-tIs
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None d... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-roberta-upper-tIs", "results": []}]} | paola-md/recipe-roberta-upper-tIs | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:51:08+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| recipe-roberta-upper-tIs
========================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7904
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: 256\n* eval\\_batch\\_size: 256\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20\n* mixed\\_p... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #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\\_size: 256\n* eval\\_batch\... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_r-wav2vec2_s732
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_r-wav2vec2_s732 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:54:29+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_r-wav2vec2_s732
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_r-wav2vec2_s732\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_r-wav2vec2_s732\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-it_s996
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-it_s996 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T18:58:21+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-it_s996
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-it_s996\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-it_s996\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-it_s738
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-it_s738 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T19:08:31+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-it_s738
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-it_s738\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-it_s738\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
tabular-classification | sklearn |
## Baseline Model trained on train5a1e8w7 to apply classification on label
**Metrics of the best model:**
accuracy 0.693101
recall_macro 0.665973
precision_macro 0.657625
f1_macro 0.656998
Name: LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000), dtype: float64
**Se... | {"license": "apache-2.0", "library_name": "sklearn", "tags": ["tabular-classification", "baseline-trainer"]} | sahilrajpal121/train5a1e8w7-label-classification | null | [
"sklearn",
"tabular-classification",
"baseline-trainer",
"license:apache-2.0",
"region:us"
] | null | 2022-07-11T19:11:07+00:00 | [] | [] | TAGS
#sklearn #tabular-classification #baseline-trainer #license-apache-2.0 #region-us
|
## Baseline Model trained on train5a1e8w7 to apply classification on label
Metrics of the best model:
accuracy 0.693101
recall_macro 0.665973
precision_macro 0.657625
f1_macro 0.656998
Name: LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000), dtype: float64
See mode... | [
"## Baseline Model trained on train5a1e8w7 to apply classification on label\n\nMetrics of the best model:\n\naccuracy 0.693101\n\nrecall_macro 0.665973\n\nprecision_macro 0.657625\n\nf1_macro 0.656998\n\nName: LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000), dtype: flo... | [
"TAGS\n#sklearn #tabular-classification #baseline-trainer #license-apache-2.0 #region-us \n",
"## Baseline Model trained on train5a1e8w7 to apply classification on label\n\nMetrics of the best model:\n\naccuracy 0.693101\n\nrecall_macro 0.665973\n\nprecision_macro 0.657625\n\nf1_macro ... |
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. -->
# t5-end2end-questions-generation
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the squad_mod... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad_modified_for_t5_qg"], "model-index": [{"name": "t5-end2end-questions-generation", "results": []}]} | camilag/t5-end2end-questions-generation | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:squad_modified_for_t5_qg",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T19:12:30+00:00 | [] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-squad_modified_for_t5_qg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| t5-end2end-questions-generation
===============================
This model is a fine-tuned version of t5-base on the squad\_modified\_for\_t5\_qg dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7927
Model description
-----------------
More information needed
Intended uses & limitat... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-squad_modified_for_t5_qg #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... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | skr1125/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T19:17:40+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2253
* Accuracy: 0.927
* F1: 0.9268
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
automatic-speech-recognition | transformers | # exp_w2v2t_pt_vp-it_s529
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition using the train split of [Common Voice 7.0 (pt)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "pt"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_pt_vp-it_s529 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T19:20:26+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_pt_vp-it_s529
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
| [
"# exp_w2v2t_pt_vp-it_s529\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (pt).\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned by the HuggingSound tool."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #pt #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_pt_vp-it_s529\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
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. -->
# pegasus-samsum
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_da... | {"tags": ["generated_from_trainer"], "datasets": ["samsum"], "model-index": [{"name": "pegasus-samsum", "results": []}]} | ManqingLiu/pegasus-samsum | null | [
"transformers",
"pytorch",
"tensorboard",
"pegasus",
"text2text-generation",
"generated_from_trainer",
"dataset:samsum",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T20:16:06+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #pegasus #text2text-generation #generated_from_trainer #dataset-samsum #autotrain_compatible #endpoints_compatible #region-us
| pegasus-samsum
==============
This model is a fine-tuned version of google/pegasus-cnn\_dailymail on the samsum dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4858
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* gradient\\_accumulation\\_steps: 16\n* total\\_train\\_batch\\_size: 16\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=... | [
"TAGS\n#transformers #pytorch #tensorboard #pegasus #text2text-generation #generated_from_trainer #dataset-samsum #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\\_batch\\... |
reinforcement-learning | sample-factory |
A(n) **APPO** model trained on the **mujoco_ant** environment.
This model was trained using Sample Factory 2.0: https://github.com/alex-petrenko/sample-factory
| {"library_name": "sample-factory", "tags": ["deep-reinforcement-learning", "reinforcement-learning", "sample-factory"], "model-index": [{"name": "APPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "mujoco_ant", "type": "mujoco_ant"}, "metrics": [{"type"... | andrewzhang505/sample-factory-2-mujoco-ant | null | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T20:41:16+00:00 | [] | [] | TAGS
#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
A(n) APPO model trained on the mujoco_ant environment.
This model was trained using Sample Factory 2.0: URL
| [] | [
"TAGS\n#sample-factory #tensorboard #deep-reinforcement-learning #reinforcement-learning #model-index #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-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | Ahmed007/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T20:49:00+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1413
* Accuracy: 0.937
* F1: 0.9372
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
text-classification | transformers | Este modelo foi treinado com o objetivo de ser utilizado para retreinar o modelo [BERT](https://huggingface.co/anatel/bert-augmented-pt-anatel) para a tarefa de similaridade, mesmo com poucos exemplos rotulados. Adotamos a estratégia [Augmented Bert](https://www.sbert.net/examples/training/data_augmentation/README.html... | {} | anatel/cross-encoder-pt-anatel-metadados-assunto | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T21:01:21+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us
| Este modelo foi treinado com o objetivo de ser utilizado para retreinar o modelo BERT para a tarefa de similaridade, mesmo com poucos exemplos rotulados. Adotamos a estratégia Augmented Bert. Treinamos o modelo cross-encoder com a base rotulada.
Config :
| [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text2text-generation | transformers |
# Model Card of `lmqg/mt5-base-esquad-qg`
This model is fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) for question generation task on the [lmqg/qg_esquad](https://huggingface.co/datasets/lmqg/qg_esquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-gener... | {"language": "es", "license": "cc-by-4.0", "tags": ["question generation"], "datasets": ["lmqg/qg_esquad"], "metrics": ["bleu4", "meteor", "rouge-l", "bertscore", "moverscore"], "pipeline_tag": "text2text-generation", "widget": [{"text": "del <hl> Ministerio de Desarrollo Urbano <hl> , Gobierno de la India.", "example_... | lmqg/mt5-base-esquad-qg | null | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"question generation",
"es",
"dataset:lmqg/qg_esquad",
"arxiv:2210.03992",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T21:02:10+00:00 | [
"2210.03992"
] | [
"es"
] | TAGS
#transformers #pytorch #mt5 #text2text-generation #question generation #es #dataset-lmqg/qg_esquad #arxiv-2210.03992 #license-cc-by-4.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Model Card of 'lmqg/mt5-base-esquad-qg'
=======================================
This model is fine-tuned version of google/mt5-base for question generation task on the lmqg/qg\_esquad (dataset\_name: default) via 'lmqg'.
### Overview
* Language model: google/mt5-base
* Language: es
* Training data: lmqg/qg\_esqua... | [
"### Overview\n\n\n* Language model: google/mt5-base\n* Language: es\n* Training data: lmqg/qg\\_esquad (default)\n* Online Demo: URL\n* Repository: URL\n* Paper: URL",
"### Usage\n\n\n* With 'lmqg'\n* With 'transformers'\n\n\nEvaluation\n----------\n\n\n* *Metric (Question Generation)*: raw metric file\n\n\n\n* ... | [
"TAGS\n#transformers #pytorch #mt5 #text2text-generation #question generation #es #dataset-lmqg/qg_esquad #arxiv-2210.03992 #license-cc-by-4.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Overview\n\n\n* Language model: google/mt5-base\n* Language: es\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
```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... | AntiSquid/longTEST2ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T21:09:16+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comple... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | mariastull/testpyramidsrnd | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2022-07-11T21:28:40+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the trainin... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the t... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documen... |
token-classification | transformers | # tner/roberta-base-tweetner7-all
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_all` split).
Model fine-tuning is done via [T-NER](https://github.com/asahi417/tner)'s hyper-parameter sea... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/roberta-base-tweetner7-all | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T21:33:41+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/roberta-base-tweetner7-all
This model is a fine-tuned version of roberta-base on the
tner/tweetner7 dataset ('train_all' split).
Model fine-tuning is done via T-NER's hyper-parameter search (see the repository
for more detail). It achieves the following results on the test set of 2021:
- F1 (micro): 0.65158318... | [
"# tner/roberta-base-tweetner7-all\n\nThis model is a fine-tuned version of roberta-base on the \ntner/tweetner7 dataset ('train_all' split).\nModel fine-tuning is done via T-NER's hyper-parameter search (see the repository\nfor more detail). It achieves the following results on the test set of 2021:\n- F1 (micro):... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/roberta-base-tweetner7-all\n\nThis model is a fine-tuned version of roberta-base on the \ntner/tweetner7 dataset ('train_all' split).\nModel fine-tu... |
token-classification | transformers | # tner/bertweet-large-tweetner7-random
This model is a fine-tuned version of [vinai/bertweet-large](https://huggingface.co/vinai/bertweet-large) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_random` split).
Model fine-tuning is done via [T-NER](https://github.com/asahi417/tne... | {"datasets": ["tner/tweetner7"], "metrics": ["f1", "precision", "recall"], "pipeline_tag": "token-classification", "widget": [{"text": "Get the all-analog Classic Vinyl Edition of `Takin' Off` Album from {@herbiehancock@} via {@bluenoterecords@} link below: {{URL}}", "example_title": "NER Example 1"}], "model-index": [... | tner/bertweet-large-tweetner7-random | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T21:50:06+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bertweet-large-tweetner7-random
This model is a fine-tuned version of vinai/bertweet-large on the
tner/tweetner7 dataset ('train_random' split).
Model fine-tuning is done via T-NER's hyper-parameter search (see the repository
for more detail). It achieves the following results on the test set of 2021:
- F1 (mi... | [
"# tner/bertweet-large-tweetner7-random\n\nThis model is a fine-tuned version of vinai/bertweet-large on the \ntner/tweetner7 dataset ('train_random' split).\nModel fine-tuning is done via T-NER's hyper-parameter search (see the repository\nfor more detail). It achieves the following results on the test set of 2021... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bertweet-large-tweetner7-random\n\nThis model is a fine-tuned version of vinai/bertweet-large on the \ntner/tweetner7 dataset ('train_random' split)... |
reinforcement-learning | transformers |
# PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# Hyperparameters
```python
{'exp_name': 'ppo'
'seed': 1
'torch_deterministic': True
'cuda': True
'track': False
'wandb_project_name': 'cleanRL'
'wandb_entity': None
'capture_video': False
'env_id': 'Lunar... | {"tags": ["LunarLander-v2", "ppo", "deep-reinforcement-learning", "reinforcement-learning", "custom-implementation", "deep-rl-course"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarLander-v2... | AntiSquid/PPO-LunarLander-v2 | null | [
"transformers",
"tensorboard",
"LunarLander-v2",
"ppo",
"deep-reinforcement-learning",
"reinforcement-learning",
"custom-implementation",
"deep-rl-course",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T22:45:10+00:00 | [] | [] | TAGS
#transformers #tensorboard #LunarLander-v2 #ppo #deep-reinforcement-learning #reinforcement-learning #custom-implementation #deep-rl-course #model-index #endpoints_compatible #region-us
|
# PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# Hyperparameters
| [
"# PPO Agent Playing LunarLander-v2\n\n This is a trained model of a PPO agent playing LunarLander-v2.\n \n # Hyperparameters"
] | [
"TAGS\n#transformers #tensorboard #LunarLander-v2 #ppo #deep-reinforcement-learning #reinforcement-learning #custom-implementation #deep-rl-course #model-index #endpoints_compatible #region-us \n",
"# PPO Agent Playing LunarLander-v2\n\n This is a trained model of a PPO agent playing LunarLander-v2.\n \n # H... |
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. -->
# recipe-distilbert-upper-Is
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-bas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-distilbert-upper-Is", "results": []}]} | paola-md/recipe-distilbert-upper-Is | null | [
"transformers",
"pytorch",
"distilbert",
"fill-mask",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T23:16:41+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| recipe-distilbert-upper-Is
==========================
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: 0.8565
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: 256\n* eval\\_batch\\_size: 256\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20\n* mixed\\_p... | [
"TAGS\n#transformers #pytorch #distilbert #fill-mask #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\\_size: 256\n* eva... |
text-classification | transformers | # DistilBERT on ArXiv
This model was developed to predict the top-level category of a paper, given the
paper's abstract, title, and list of authors. It was trained over a subset of
data pulled from the ArXiv API.
| {"language": "en", "license": "apache-2.0", "tags": ["arxiv", "topic-classification", "distilbert"], "widget": [{"text": "Title: ImageNet classification with deep convolutional neural networks\n Abstract: We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the Ima... | Wi/arxiv-topics-distilbert-base-cased | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"arxiv",
"topic-classification",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T23:43:06+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #distilbert #text-classification #arxiv #topic-classification #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| # DistilBERT on ArXiv
This model was developed to predict the top-level category of a paper, given the
paper's abstract, title, and list of authors. It was trained over a subset of
data pulled from the ArXiv API.
| [
"# DistilBERT on ArXiv\n\nThis model was developed to predict the top-level category of a paper, given the\npaper's abstract, title, and list of authors. It was trained over a subset of\ndata pulled from the ArXiv API."
] | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #arxiv #topic-classification #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# DistilBERT on ArXiv\n\nThis model was developed to predict the top-level category of a paper, given the\npaper's abstract, title, and l... |
null | keras |
# Model Card for my-cool-model
<!-- Provide a quick summary of what the model is/does. -->
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training Details](#training-details)
5. [Evaluation](#evaluation)
6. [Model Examinati... | {"language": "en", "license": "mit", "library_name": "keras"} | nateraw/hf-hub-modelcards-pr-test | null | [
"keras",
"en",
"arxiv:1910.09700",
"license:mit",
"region:us"
] | null | 2022-07-12T00:06:55+00:00 | [
"1910.09700"
] | [
"en"
] | TAGS
#keras #en #arxiv-1910.09700 #license-mit #region-us
|
# Model Card for my-cool-model
# Table of Contents
1. Model Details
2. Uses
3. Bias, Risks, and Limitations
4. Training Details
5. Evaluation
6. Model Examination
7. Environmental Impact
8. Technical Specifications
9. Citation
10. Glossary
11. More Information
12. Model Card Authors
13. Model Card Contact
14. How... | [
"# Model Card for my-cool-model",
"# Table of Contents\n\n1. Model Details\n2. Uses\n3. Bias, Risks, and Limitations\n4. Training Details\n5. Evaluation\n6. Model Examination\n7. Environmental Impact\n8. Technical Specifications\n9. Citation\n10. Glossary\n11. More Information\n12. Model Card Authors\n13. Model ... | [
"TAGS\n#keras #en #arxiv-1910.09700 #license-mit #region-us \n",
"# Model Card for my-cool-model",
"# Table of Contents\n\n1. Model Details\n2. Uses\n3. Bias, Risks, and Limitations\n4. Training Details\n5. Evaluation\n6. Model Examination\n7. Environmental Impact\n8. Technical Specifications\n9. Citation\n10.... |
null | null |
### How to clone this repo
```
sudo apt-get install git-lfs
git clone https://huggingface.co/yuekai/icefall-asr-aishell2-pruned-transducer-stateless5-B-2022-07-12
cd https://huggingface.co/yuekai/icefall-asr-aishell2-pruned-transducer-stateless5-B-2022-07-12
git lfs pull
```
| {"license": "apache-2.0"} | yuekai/icefall-asr-aishell2-pruned-transducer-stateless5-B-2022-07-12 | null | [
"license:apache-2.0",
"has_space",
"region:us"
] | null | 2022-07-12T00:54:35+00:00 | [] | [] | TAGS
#license-apache-2.0 #has_space #region-us
|
### How to clone this repo
| [
"### How to clone this repo"
] | [
"TAGS\n#license-apache-2.0 #has_space #region-us \n",
"### How to clone this repo"
] |
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/1147337070920097793/06CZ... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/hhelafifi/1657594186366/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/hhelafifi | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-12T01:32:46+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Hussein
@hhelafifi
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
-------------
... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
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. -->
# recipe-distilbert-s
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-distilbert-s", "results": []}]} | paola-md/recipe-distilbert-s | null | [
"transformers",
"pytorch",
"distilbert",
"fill-mask",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-12T02:06:52+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| recipe-distilbert-s
===================
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: 1.0321
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: 256\n* eval\\_batch\\_size: 256\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20\n* mixed\\_p... | [
"TAGS\n#transformers #pytorch #distilbert #fill-mask #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\\_size: 256\n* eva... |
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. -->
# finetuned-mt5-base-10epoch
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on th... | {"language": ["en", "ro"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wmt16"], "model-index": [{"name": "finetuned-mt5-base-10epoch", "results": []}]} | Lvxue/finetuned-mt5-base-10epoch | null | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"generated_from_trainer",
"en",
"ro",
"dataset:wmt16",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-12T02:18:31+00:00 | [] | [
"en",
"ro"
] | TAGS
#transformers #pytorch #mt5 #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# finetuned-mt5-base-10epoch
This model is a fine-tuned version of google/mt5-base on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2607
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation d... | [
"# finetuned-mt5-base-10epoch\n\nThis model is a fine-tuned version of google/mt5-base on the wmt16 ro-en dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 1.2607",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Tra... | [
"TAGS\n#transformers #pytorch #mt5 #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# finetuned-mt5-base-10epoch\n\nThis model is a fine-tuned version of google/mt5-base on the wmt16 ro-... |
multiple-choice | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# medqa_fine_tuned
This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/Bio... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "medqa_fine_tuned", "results": []}]} | Shaier/medqa_fine_tuned_linkbert | null | [
"transformers",
"pytorch",
"bert",
"multiple-choice",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-12T02:27:12+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #multiple-choice #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| medqa\_fine\_tuned
==================
This model is a fine-tuned version of michiyasunaga/BioLinkBERT-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4462
* Accuracy: 0.4002
Model description
-----------------
More information needed
Intended uses & limitations
-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\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=1... | [
"TAGS\n#transformers #pytorch #bert #multiple-choice #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* s... |
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. -->
# legalectra-small-spanish-becasv3-1
This model is a fine-tuned version of [mrm8488/legalectra-small-spanish](https://huggingface.... | {"tags": ["generated_from_trainer"], "datasets": ["becasv2"], "model-index": [{"name": "legalectra-small-spanish-becasv3-1", "results": []}]} | Evelyn18/legalectra-small-spanish-becasv3-1 | null | [
"transformers",
"pytorch",
"tensorboard",
"electra",
"question-answering",
"generated_from_trainer",
"dataset:becasv2",
"endpoints_compatible",
"region:us"
] | null | 2022-07-12T02:49:49+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #electra #question-answering #generated_from_trainer #dataset-becasv2 #endpoints_compatible #region-us
| legalectra-small-spanish-becasv3-1
==================================
This model is a fine-tuned version of mrm8488/legalectra-small-spanish on the becasv2 dataset.
It achieves the following results on the evaluation set:
* Loss: 5.5694
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 10\n* eval\\_batch\\_size: 10\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 10",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #electra #question-answering #generated_from_trainer #dataset-becasv2 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 10\n* eval\\_bat... |
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. -->
# legalectra-small-spanish-becasv3-2
This model is a fine-tuned version of [mrm8488/legalectra-small-spanish](https://huggingface.... | {"tags": ["generated_from_trainer"], "datasets": ["becasv2"], "model-index": [{"name": "legalectra-small-spanish-becasv3-2", "results": []}]} | Evelyn18/legalectra-small-spanish-becasv3-2 | null | [
"transformers",
"pytorch",
"tensorboard",
"electra",
"question-answering",
"generated_from_trainer",
"dataset:becasv2",
"endpoints_compatible",
"region:us"
] | null | 2022-07-12T03:00:10+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #electra #question-answering #generated_from_trainer #dataset-becasv2 #endpoints_compatible #region-us
| legalectra-small-spanish-becasv3-2
==================================
This model is a fine-tuned version of mrm8488/legalectra-small-spanish on the becasv2 dataset.
It achieves the following results on the evaluation set:
* Loss: 4.7145
Model description
-----------------
More information needed
Intended uses... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-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: 30",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #electra #question-answering #generated_from_trainer #dataset-becasv2 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_bat... |
fill-mask | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# reecejocumsenbb/testfield-finetuned-imdb
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distil... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "reecejocumsenbb/testfield-finetuned-imdb", "results": []}]} | reecejocumsenbb/testfield-finetuned-imdb | null | [
"transformers",
"tf",
"distilbert",
"fill-mask",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-12T03:23:21+00:00 | [] | [] | TAGS
#transformers #tf #distilbert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| reecejocumsenbb/testfield-finetuned-imdb
========================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 4.0451
* Validation Loss: 3.9664
* Epoch: 0
Model description
--------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'WarmUp', 'config': {'initial\\_learning\\_rate': 2e-05, 'decay\\_schedule\\_fn': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_le... | [
"TAGS\n#transformers #tf #distilbert #fill-mask #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate'... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.