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automatic-speech-recognition | transformers | # exp_w2v2t_ru_unispeech-ml_s947
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_unispeech-ml_s947 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T07:44:54+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_unispeech-ml_s947
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_unispeech-ml_s947\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_unispeech-ml_s947\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_unispeech-ml_s569
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_unispeech-ml_s569 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T07:48:11+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_unispeech-ml_s569
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_unispeech-ml_s569\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_unispeech-ml_s569\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
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-Is
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None da... | {"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "recipe-roberta-upper-Is", "results": []}]} | paola-md/recipe-roberta-upper-Is | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T07:50:33+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| recipe-roberta-upper-Is
=======================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7757
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_ru_unispeech-ml_s253
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_unispeech-ml_s253 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T07:51:11+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_unispeech-ml_s253
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_unispeech-ml_s253\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_unispeech-ml_s253\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-fr_s930
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-fr_s930 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T07:54:29+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-fr_s930
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-fr_s930\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-fr_s930\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-fr_s730
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-fr_s730 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T07:58:02+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-fr_s730
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-fr_s730\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-fr_s730\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-fr_s805
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-fr_s805 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:01:05+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-fr_s805
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-fr_s805\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-fr_s805\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-es_s729
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-es_s729 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:04:06+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-es_s729
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-es_s729\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-es_s729\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-es_s664
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-es_s664 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:07:23+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-es_s664
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-es_s664\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-es_s664\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-es_s35
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-es_s35 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:10:26+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-es_s35
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-es_s35\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-es_s35\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-nl_s328
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-nl_s328 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:13:23+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-nl_s328
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-nl_s328\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-nl_s328\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-nl_s131
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-nl_s131 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:16:37+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-nl_s131
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-nl_s131\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-nl_s131\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-nl_s624
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-nl_s624 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:19:47+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-nl_s624
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-nl_s624\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-nl_s624\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_unispeech-sat_s423
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_unispeech-sat_s423 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:22:56+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_unispeech-sat_s423
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_unispeech-sat_s423\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_unispeech-sat_s423\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_unispeech-sat_s418
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_unispeech-sat_s418 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:26:11+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_unispeech-sat_s418
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_unispeech-sat_s418\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_unispeech-sat_s418\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_unispeech-sat_s160
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_unispeech-sat_s160 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:29:28+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_unispeech-sat_s160
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_unispeech-sat_s160\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_unispeech-sat_s160\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_xls-r_s884
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_xls-r_s884 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:34:12+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_xls-r_s884
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_xls-r_s884\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_xls-r_s884\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (r... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_xls-r_s635
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_xls-r_s635 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:42:14+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_xls-r_s635
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_xls-r_s635\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_xls-r_s635\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (r... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_xls-r_s946
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_xls-r_s946 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:46:39+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_xls-r_s946
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_xls-r_s946\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_xls-r_s946\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (r... |
token-classification | null |
**task**: `token-classification`
**Backend:** `sagemaker-training`
**Backend args:** `{'instance_type': 'ml.m5.2xlarge', 'supported_instructions': 'avx512'}`
**Number of evaluation samples:** `10`
Fixed parameters:
* **model_name_or_path**: `elastic/distilbert-base-uncased-finetuned-conll03-english`
* **datas... | {"tags": ["distilbert"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "pipeline_tag": "token-classification"} | fxmarty/20220711-h09m49s39_example_conll2003 | null | [
"tensorboard",
"distilbert",
"token-classification",
"dataset:conll2003",
"region:us"
] | null | 2022-07-11T08:49:39+00:00 | [] | [] | TAGS
#tensorboard #distilbert #token-classification #dataset-conll2003 #region-us
| task: 'token-classification'
Backend: 'sagemaker-training'
Backend args: '{'instance\_type': 'ml.m5.2xlarge', 'supported\_instructions': 'avx512'}'
Number of evaluation samples: '10'
Fixed parameters:
* model\_name\_or\_path: 'elastic/distilbert-base-uncased-finetuned-conll03-english'
* dataset:
+ path: '... | [] | [
"TAGS\n#tensorboard #distilbert #token-classification #dataset-conll2003 #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_r-wav2vec2_s399
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_r-wav2vec2_s399 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:49:58+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_r-wav2vec2_s399
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_r-wav2vec2_s399\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_r-wav2vec2_s399\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_r-wav2vec2_s408
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_r-wav2vec2_s408 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:53:13+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_r-wav2vec2_s408
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_r-wav2vec2_s408\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_r-wav2vec2_s408\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_r-wav2vec2_s869
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_r-wav2vec2_s869 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:56:07+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_r-wav2vec2_s869
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_r-wav2vec2_s869\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_r-wav2vec2_s869\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
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... | AliMMZ/first_RL | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T08:56:49+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\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... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-it_s817
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-it_s817 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T08:59:26+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-it_s817
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-it_s817\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-it_s817\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
token-classification | null |
**task**: `token-classification`
**Backend:** `sagemaker-training`
**Backend args:** `{'instance_type': 'ml.m5.2xlarge', 'supported_instructions': 'avx512'}`
**Number of evaluation samples:** `100`
Fixed parameters:
* **model_name_or_path**: `elastic/distilbert-base-uncased-finetuned-conll03-english`
* **data... | {"tags": ["distilbert"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "pipeline_tag": "token-classification"} | fxmarty/20220711-h10m00s56_example_conll2003 | null | [
"tensorboard",
"distilbert",
"token-classification",
"dataset:conll2003",
"region:us"
] | null | 2022-07-11T09:00:56+00:00 | [] | [] | TAGS
#tensorboard #distilbert #token-classification #dataset-conll2003 #region-us
| task: 'token-classification'
Backend: 'sagemaker-training'
Backend args: '{'instance\_type': 'ml.m5.2xlarge', 'supported\_instructions': 'avx512'}'
Number of evaluation samples: '100'
Fixed parameters:
* model\_name\_or\_path: 'elastic/distilbert-base-uncased-finetuned-conll03-english'
* dataset:
+ path: ... | [] | [
"TAGS\n#tensorboard #distilbert #token-classification #dataset-conll2003 #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-it_s975
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-it_s975 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:03:23+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-it_s975
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-it_s975\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-it_s975\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voic... |
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... | wooihen/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 | 2022-07-11T09:04:15+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: 0.2146
* Accuracy: 0.9225
* F1: 0.9228
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... |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}]} | GhostZen/distilbert-base-uncased-finetuned-squad | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:09:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of distilbert-base-uncased on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### ... | [
"# distilbert-base-uncased-finetuned-squad\n\nThis model is a fine-tuned version of distilbert-base-uncased on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"#... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# distilbert-base-uncased-finetuned-squad\n\nThis model is a fine-tuned version of distilbert-base-uncased on the squad dataset.",
"## Mode... |
automatic-speech-recognition | transformers | # exp_w2v2t_ru_vp-it_s533
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 (ru)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "ru"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_ru_vp-it_s533 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:09:12+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_ru_vp-it_s533
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).
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_ru_vp-it_s533\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition using the train split of Common Voice 7.0 (ru).\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 #ru #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_ru_vp-it_s533\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_wav2vec2_s877
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_wav2vec2_s877 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:12:13+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_wav2vec2_s877
Fine-tuned facebook/wav2vec2-large-lv60 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_wav2vec2_s877\n\nFine-tuned facebook/wav2vec2-large-lv60 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_wav2vec2_s877\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_es_wav2vec2_s596
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_wav2vec2_s596 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:15:16+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_wav2vec2_s596
Fine-tuned facebook/wav2vec2-large-lv60 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_wav2vec2_s596\n\nFine-tuned facebook/wav2vec2-large-lv60 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_wav2vec2_s596\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_es_wav2vec2_s875
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inp... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_wav2vec2_s875 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:18:46+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_wav2vec2_s875
Fine-tuned facebook/wav2vec2-large-lv60 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_wav2vec2_s875\n\nFine-tuned facebook/wav2vec2-large-lv60 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_wav2vec2_s875\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_es_vp-100k_s957
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-100k_s957 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:22:18+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-100k_s957
Fine-tuned facebook/wav2vec2-large-100k-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-100k_s957\n\nFine-tuned facebook/wav2vec2-large-100k-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-100k_s957\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-100k_s468
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-100k_s468 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:25:51+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-100k_s468
Fine-tuned facebook/wav2vec2-large-100k-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-100k_s468\n\nFine-tuned facebook/wav2vec2-large-100k-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-100k_s468\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-100k_s732
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-100k_s732 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:28:53+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-100k_s732
Fine-tuned facebook/wav2vec2-large-100k-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-100k_s732\n\nFine-tuned facebook/wav2vec2-large-100k-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-100k_s732\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition using the train split of Common ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_xlsr-53_s377
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_xlsr-53_s377 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:32:11+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_xlsr-53_s377
Fine-tuned facebook/wav2vec2-large-xlsr-53 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_xlsr-53_s377\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 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_xlsr-53_s377\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_es_xlsr-53_s756
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_xlsr-53_s756 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:35:16+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_xlsr-53_s756
Fine-tuned facebook/wav2vec2-large-xlsr-53 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_xlsr-53_s756\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 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_xlsr-53_s756\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition using the train split of Common Voice 7... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# clinical_bert_ft
This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/B... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "clinical_bert_ft", "results": []}]} | ericntay/clinical_bert_ft | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:38:42+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| clinical\_bert\_ft
==================
This model is a fine-tuned version of emilyalsentzer/Bio\_ClinicalBERT on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2439
* F1: 0.8252
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: 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: 10",
"### Train... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #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: 5e-05\n* train\\_batch\\_size:... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_xlsr-53_s103
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speec... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_xlsr-53_s103 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:39:11+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_xlsr-53_s103
Fine-tuned facebook/wav2vec2-large-xlsr-53 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_xlsr-53_s103\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 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_xlsr-53_s103\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_es_unispeech_s990
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 (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_unispeech_s990 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:42:38+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech_s990
Fine-tuned microsoft/unispeech-large-1500h-cv 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_s990\n\nFine-tuned microsoft/unispeech-large-1500h-cv 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 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech_s990\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech_s767
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 (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_unispeech_s767 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:45:56+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech_s767
Fine-tuned microsoft/unispeech-large-1500h-cv 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_s767\n\nFine-tuned microsoft/unispeech-large-1500h-cv 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 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech_s767\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
token-classification | transformers | # tner/bert-base-tweetner7-random
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) 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/tner)'s hyper-para... | {"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/bert-base-tweetner7-random | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:46:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bert-base-tweetner7-random
This model is a fine-tuned version of bert-base-cased 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 (micro): 0.60... | [
"# tner/bert-base-tweetner7-random\n\nThis model is a fine-tuned version of bert-base-cased 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:\n- F1 (m... | [
"TAGS\n#transformers #pytorch #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bert-base-tweetner7-random\n\nThis model is a fine-tuned version of bert-base-cased on the \ntner/tweetner7 dataset ('train_random' split).\nModel fine... |
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. -->
# reformer-finetuned-big_patent-16384
This model is a fine-tuned version of [robingeibel/reformer-finetuned-big_patent-wikipedia-a... | {"tags": ["generated_from_trainer"], "datasets": ["big_patent"], "model-index": [{"name": "reformer-finetuned-big_patent-16384", "results": []}]} | robingeibel/reformer-finetuned-big_patent-16384 | null | [
"transformers",
"pytorch",
"tensorboard",
"reformer",
"fill-mask",
"generated_from_trainer",
"dataset:big_patent",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:48:37+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #reformer #fill-mask #generated_from_trainer #dataset-big_patent #autotrain_compatible #endpoints_compatible #region-us
| reformer-finetuned-big\_patent-16384
====================================
This model is a fine-tuned version of robingeibel/reformer-finetuned-big\_patent-wikipedia-arxiv-16384 on the big\_patent dataset.
It achieves the following results on the evaluation set:
* Loss: 6.7382
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2.5e-06\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3.0\n* mixed\\_pr... | [
"TAGS\n#transformers #pytorch #tensorboard #reformer #fill-mask #generated_from_trainer #dataset-big_patent #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2.5e-06\n* train\\_batch\\_siz... |
text2text-generation | transformers | T5-base fine-tuned on CNN/DM Summarization dataset.
Training args:
```
{
"learning_rate": 0.0001,
"logging_steps": 5000,
"lr_scheduler_type": "cosine",
"num_train_epochs": 2,
"per_device_train_batch_size": 16, # total batch size of 48
"save_total... | {"license": "apache-2.0"} | rajkumarrrk/t5-base-fine-tuned-on-cnn-dm | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T09:48:43+00:00 | [] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| T5-base fine-tuned on CNN/DM Summarization dataset.
Training args:
Generation kwargs:
'
Pre-processing: Append prompt with prefix "Summarize: "
Post-processing: None
Test split metrics:
| [] | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech_s461
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 (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_unispeech_s461 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:49:09+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech_s461
Fine-tuned microsoft/unispeech-large-1500h-cv 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_s461\n\nFine-tuned microsoft/unispeech-large-1500h-cv 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 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech_s461\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition using the train split of Common V... |
text-generation | transformers |
GPT-2 fine-tuned on CNN/DM summarization dataset.
Training args:\
{
"learning_rate": 0.0001\
"logging_steps": 5000\
"lr_scheduler_type": "cosine"\
"num_train_epochs": 2\
"per_device_train_batch_size": 12, # Total batch size: 36\
"weight_decay": 0.1\
}
{"generation_kwargs": {"do_sample": true, "max_new_tokens": 100, ... | {"license": "apache-2.0"} | rajkumarrrk/gpt-2-fine-tuned-on-cnn-dm | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T09:51:53+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
GPT-2 fine-tuned on CNN/DM summarization dataset.
Training args:\
{
"learning_rate": 0.0001\
"logging_steps": 5000\
"lr_scheduler_type": "cosine"\
"num_train_epochs": 2\
"per_device_train_batch_size": 12, # Total batch size: 36\
"weight_decay": 0.1\
}
{"generation_kwargs": {"do_sample": true, "max_new_tokens": 100, ... | [
"# Total batch size: 36\\\n\"weight_decay\": 0.1\\\n}\n\n{\"generation_kwargs\": {\"do_sample\": true, \"max_new_tokens\": 100, \"min_length\": 50}\n\nPre-processing to truncate the article to contain only 500 tokens.\nPost-processing to consider only first three sentences as the summary.\n\nTest split metrics:\n\n... | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Total batch size: 36\\\n\"weight_decay\": 0.1\\\n}\n\n{\"generation_kwargs\": {\"do_sample\": true, \"max_new_tokens\": 100, \"min_length\": 50}\n\nPre... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_hubert_s459
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 (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_hubert_s459 | null | [
"transformers",
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"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:52:20+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_hubert_s459
Fine-tuned facebook/hubert-large-ll60k 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_hubert_s459\n\nFine-tuned facebook/hubert-large-ll60k 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 #hubert #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_hubert_s459\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (es)... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_hubert_s456
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 (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_hubert_s456 | null | [
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"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:55:43+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_hubert_s456
Fine-tuned facebook/hubert-large-ll60k 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_hubert_s456\n\nFine-tuned facebook/hubert-large-ll60k 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 #hubert #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_hubert_s456\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (es)... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_hubert_s251
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 (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_hubert_s251 | null | [
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"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T09:59:03+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_hubert_s251
Fine-tuned facebook/hubert-large-ll60k 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_hubert_s251\n\nFine-tuned facebook/hubert-large-ll60k 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 #hubert #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_hubert_s251\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition using the train split of Common Voice 7.0 (es)... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-sv_s863
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 (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-sv_s863 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:02:29+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-sv_s863
Fine-tuned facebook/wav2vec2-large-sv-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-sv_s863\n\nFine-tuned facebook/wav2vec2-large-sv-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-sv_s863\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voic... |
text-generation | transformers | ### Quantized bigscience/bloom with 8-bit weights
Heavily inspired by [Hivemind's GPT-J-6B with 8-bit weights](https://huggingface.co/hivemind/gpt-j-6B-8bit), this is a version of [bigscience/bloom](https://huggingface.co/bigscience/bloom) a ~176 billion parameters language model that you run and fine-tune with less m... | {"language": ["ak", "ar", "as", "bm", "bn", "ca", "en", "es", "eu", "fon", "fr", "gu", "hi", "id", "ig", "ki", "kn", "lg", "ln", "ml", "mr", "ne", "nso", "ny", "or", "pa", "pt", "rn", "rw", "sn", "st", "sw", "ta", "te", "tn", "ts", "tum", "tw", "ur", "vi", "wo", "xh", "yo", "zh", "zu"], "license": "bigscience-bloom-rai... | joaoalvarenga/bloom-8bit | null | [
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"... | TAGS
#transformers #pytorch #bloom #text-generation #ak #ar #as #bm #bn #ca #en #es #eu #fon #fr #gu #hi #id #ig #ki #kn #lg #ln #ml #mr #ne #nso #ny #or #pa #pt #rn #rw #sn #st #sw #ta #te #tn #ts #tum #tw #ur #vi #wo #xh #yo #zh #zu #arxiv-2106.09685 #license-bigscience-bloom-rail-1.0 #autotrain_compatible #text-gene... | ### Quantized bigscience/bloom with 8-bit weights
Heavily inspired by Hivemind's GPT-J-6B with 8-bit weights, this is a version of bigscience/bloom a ~176 billion parameters language model that you run and fine-tune with less memory.
Here, we also apply LoRA (Low Rank Adaptation) to reduce model size. The original ve... | [
"### Quantized bigscience/bloom with 8-bit weights\n\nHeavily inspired by Hivemind's GPT-J-6B with 8-bit weights, this is a version of bigscience/bloom a ~176 billion parameters language model that you run and fine-tune with less memory.\n\nHere, we also apply LoRA (Low Rank Adaptation) to reduce model size. The or... | [
"TAGS\n#transformers #pytorch #bloom #text-generation #ak #ar #as #bm #bn #ca #en #es #eu #fon #fr #gu #hi #id #ig #ki #kn #lg #ln #ml #mr #ne #nso #ny #or #pa #pt #rn #rw #sn #st #sw #ta #te #tn #ts #tum #tw #ur #vi #wo #xh #yo #zh #zu #arxiv-2106.09685 #license-bigscience-bloom-rail-1.0 #autotrain_compatible #tex... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-sv_s44
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-sv_s44 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:07:05+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-sv_s44
Fine-tuned facebook/wav2vec2-large-sv-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-sv_s44\n\nFine-tuned facebook/wav2vec2-large-sv-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-sv_s44\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-sv_s93
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_vp-sv_s93 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:10:33+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-sv_s93
Fine-tuned facebook/wav2vec2-large-sv-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-sv_s93\n\nFine-tuned facebook/wav2vec2-large-sv-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-sv_s93\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition using the train split of Common Voice... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_no-pretraining_s445
Fine-tuned randomly initialized wav2vec2 model 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 is sampled at 16kHz.
This model has be... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_no-pretraining_s445 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:14:09+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_no-pretraining_s445
Fine-tuned randomly initialized wav2vec2 model 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_no-pretraining_s445\n\nFine-tuned randomly initialized wav2vec2 model 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_no-pretraining_s445\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Com... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_no-pretraining_s807
Fine-tuned randomly initialized wav2vec2 model 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 is sampled at 16kHz.
This model has be... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_no-pretraining_s807 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:17:31+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_no-pretraining_s807
Fine-tuned randomly initialized wav2vec2 model 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_no-pretraining_s807\n\nFine-tuned randomly initialized wav2vec2 model 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_no-pretraining_s807\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Com... |
token-classification | transformers | # tner/twitter-roberta-base-2019-90m-tweetner7-random
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2019-90m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_random` split).
Model fine-tun... | {"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-2019-90m-tweetner7-random | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:20:13+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/twitter-roberta-base-2019-90m-tweetner7-random
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2019-90m 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 result... | [
"# tner/twitter-roberta-base-2019-90m-tweetner7-random\n\nThis model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2019-90m 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 follow... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/twitter-roberta-base-2019-90m-tweetner7-random\n\nThis model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2019-90m on the \ntner/tweet... |
token-classification | transformers | # tner/bert-large-tweetner7-random
This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) 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/tner)'s hyper-p... | {"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/bert-large-tweetner7-random | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:22:19+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bert-large-tweetner7-random
This model is a fine-tuned version of bert-large-cased 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 (micro): 0.... | [
"# tner/bert-large-tweetner7-random\n\nThis model is a fine-tuned version of bert-large-cased 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:\n- F1 ... | [
"TAGS\n#transformers #pytorch #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bert-large-tweetner7-random\n\nThis model is a fine-tuned version of bert-large-cased on the \ntner/tweetner7 dataset ('train_random' split).\nModel fi... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_no-pretraining_s953
Fine-tuned randomly initialized wav2vec2 model 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 is sampled at 16kHz.
This model has be... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_no-pretraining_s953 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:22:50+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_no-pretraining_s953
Fine-tuned randomly initialized wav2vec2 model 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_no-pretraining_s953\n\nFine-tuned randomly initialized wav2vec2 model 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_no-pretraining_s953\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition using the train split of Com... |
token-classification | transformers | # tner/roberta-large-tweetner7-random
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-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/tner)'s hyper-para... | {"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-large-tweetner7-random | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:23:27+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/roberta-large-tweetner7-random
This model is a fine-tuned version of roberta-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 (micro): 0.... | [
"# tner/roberta-large-tweetner7-random\n\nThis model is a fine-tuned version of roberta-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:\n- F1 ... | [
"TAGS\n#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/roberta-large-tweetner7-random\n\nThis model is a fine-tuned version of roberta-large on the \ntner/tweetner7 dataset ('train_random' split).\nModel... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_wavlm_s115
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-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 speech input is sampled at ... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_wavlm_s115 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:29:51+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_wavlm_s115
Fine-tuned microsoft/wavlm-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_wavlm_s115\n\nFine-tuned microsoft/wavlm-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 #wavlm #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_wavlm_s115\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (es).\nWhen ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_wavlm_s26
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-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 speech input is sampled at 1... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_wavlm_s26 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:37:01+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_wavlm_s26
Fine-tuned microsoft/wavlm-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_wavlm_s26\n\nFine-tuned microsoft/wavlm-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 #wavlm #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_wavlm_s26\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (es).\nWhen u... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_wavlm_s655
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-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 speech input is sampled at ... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_wavlm_s655 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:43:35+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_wavlm_s655
Fine-tuned microsoft/wavlm-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_wavlm_s655\n\nFine-tuned microsoft/wavlm-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 #wavlm #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_wavlm_s655\n\nFine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (es).\nWhen ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech-ml_s186
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_unispeech-ml_s186 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:49:25+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech-ml_s186
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv 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-ml_s186\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv 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 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech-ml_s186\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech-ml_s474
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_unispeech-ml_s474 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T10:57:35+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech-ml_s474
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv 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-ml_s474\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv 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 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech-ml_s474\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech-ml_s952
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 (es)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When usin... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_unispeech-ml_s952 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T11:04:48+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_es_unispeech-ml_s952
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv 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-ml_s952\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv 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 #automatic-speech-recognition #es #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_es_unispeech-ml_s952\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition using the train ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-fr_s169
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 (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-fr_s169 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T11:17:50+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-fr_s169
Fine-tuned facebook/wav2vec2-large-fr-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-fr_s169\n\nFine-tuned facebook/wav2vec2-large-fr-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-fr_s169\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
text2text-generation | transformers |
This is [T5-base Parapharasing model](https://huggingface.co/ceshine/t5-paraphrase-paws-msrp-opinosis) fine-tuned on [GYAFC formality dataset](https://aclanthology.org/N18-1012/) in __from formal to informal direction__. So you may use this model to make your English text more informal. | {"language": "en", "license": "openrail++", "tags": ["t5", "formality transfer", "text style transfer"], "datasets": ["GYAFC"]} | s-nlp/t5-informal | null | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"formality transfer",
"text style transfer",
"en",
"dataset:GYAFC",
"license:openrail++",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T11:20:16+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #formality transfer #text style transfer #en #dataset-GYAFC #license-openrail++ #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
This is T5-base Parapharasing model fine-tuned on GYAFC formality dataset in __from formal to informal direction__. So you may use this model to make your English text more informal. | [] | [
"TAGS\n#transformers #pytorch #safetensors #t5 #text2text-generation #formality transfer #text style transfer #en #dataset-GYAFC #license-openrail++ #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **seals/HalfCheetah-v0**
This is a trained model of a **SAC** agent playing **seals/HalfCheetah-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable B... | {"library_name": "stable-baselines3", "tags": ["seals/HalfCheetah-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/HalfCheetah-v0", "ty... | ernestumorga/sac-seals-HalfCheetah-v0 | null | [
"stable-baselines3",
"seals/HalfCheetah-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:27:28+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/HalfCheetah-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing seals/HalfCheetah-v0
This is a trained model of a SAC agent playing seals/HalfCheetah-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
##... | [
"# SAC Agent playing seals/HalfCheetah-v0\nThis is a trained model of a SAC agent playing seals/HalfCheetah-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents in... | [
"TAGS\n#stable-baselines3 #seals/HalfCheetah-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing seals/HalfCheetah-v0\nThis is a trained model of a SAC agent playing seals/HalfCheetah-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a ... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **seals/Ant-v0**
This is a trained model of a **SAC** agent playing **seals/Ant-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinfo... | {"library_name": "stable-baselines3", "tags": ["seals/Ant-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/Ant-v0", "type": "seals/Ant-... | ernestumorga/sac-seals-Ant-v0 | null | [
"stable-baselines3",
"seals/Ant-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:28:37+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/Ant-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing seals/Ant-v0
This is a trained model of a SAC agent playing seals/Ant-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3... | [
"# SAC Agent playing seals/Ant-v0\nThis is a trained model of a SAC agent playing seals/Ant-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
"## ... | [
"TAGS\n#stable-baselines3 #seals/Ant-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing seals/Ant-v0\nThis is a trained model of a SAC agent playing seals/Ant-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for S... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **seals/Swimmer-v0**
This is a trained model of a **SAC** agent playing **seals/Swimmer-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines... | {"library_name": "stable-baselines3", "tags": ["seals/Swimmer-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/Swimmer-v0", "type": "se... | ernestumorga/sac-seals-Swimmer-v0 | null | [
"stable-baselines3",
"seals/Swimmer-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:30:14+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/Swimmer-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing seals/Swimmer-v0
This is a trained model of a SAC agent playing seals/Swimmer-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (... | [
"# SAC Agent playing seals/Swimmer-v0\nThis is a trained model of a SAC agent playing seals/Swimmer-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included."... | [
"TAGS\n#stable-baselines3 #seals/Swimmer-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing seals/Swimmer-v0\nThis is a trained model of a SAC agent playing seals/Swimmer-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fra... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-fr_s281
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 (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-fr_s281 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T11:31:26+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-fr_s281
Fine-tuned facebook/wav2vec2-large-fr-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-fr_s281\n\nFine-tuned facebook/wav2vec2-large-fr-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-fr_s281\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **seals/Walker2d-v0**
This is a trained model of a **SAC** agent playing **seals/Walker2d-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselin... | {"library_name": "stable-baselines3", "tags": ["seals/Walker2d-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/Walker2d-v0", "type": "... | ernestumorga/sac-seals-Walker2d-v0 | null | [
"stable-baselines3",
"seals/Walker2d-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:33:06+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/Walker2d-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing seals/Walker2d-v0
This is a trained model of a SAC agent playing seals/Walker2d-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage... | [
"# SAC Agent playing seals/Walker2d-v0\nThis is a trained model of a SAC agent playing seals/Walker2d-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included... | [
"TAGS\n#stable-baselines3 #seals/Walker2d-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing seals/Walker2d-v0\nThis is a trained model of a SAC agent playing seals/Walker2d-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training ... |
text2text-generation | transformers | `cyT5-small` is a light-weight (alpha-version) Welsh T5 model extracted from the `google/mt5-small` model and fine-tuned only on the [Welsh summarization dataset](https://huggingface.co/datasets/ignatius/welsh_summarization).
**Citation:**
[Introducing the Welsh Text Summarisation Dataset and Baseline Systems](https... | {"license": "cc-by-4.0", "datasets": "ignatius/welsh_summarization"} | ignatius/cyT5-small | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"dataset:ignatius/welsh_summarization",
"arxiv:2205.02545",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T11:35:24+00:00 | [
"2205.02545"
] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #dataset-ignatius/welsh_summarization #arxiv-2205.02545 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| 'cyT5-small' is a light-weight (alpha-version) Welsh T5 model extracted from the 'google/mt5-small' model and fine-tuned only on the Welsh summarization dataset.
Citation:
Introducing the Welsh Text Summarisation Dataset and Baseline Systems.
Further developments are ongoing and will update will be shared soon. | [] | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #dataset-ignatius/welsh_summarization #arxiv-2205.02545 #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **seals/Hopper-v0**
This is a trained model of a **SAC** agent playing **seals/Hopper-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
... | {"library_name": "stable-baselines3", "tags": ["seals/Hopper-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/Hopper-v0", "type": "seal... | ernestumorga/sac-seals-Hopper-v0 | null | [
"stable-baselines3",
"seals/Hopper-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:36:55+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/Hopper-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing seals/Hopper-v0
This is a trained model of a SAC agent playing seals/Hopper-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (wi... | [
"# SAC Agent playing seals/Hopper-v0\nThis is a trained model of a SAC agent playing seals/Hopper-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included.",
... | [
"TAGS\n#stable-baselines3 #seals/Hopper-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing seals/Hopper-v0\nThis is a trained model of a SAC agent playing seals/Hopper-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framew... |
reinforcement-learning | stable-baselines3 |
# **SAC** Agent playing **seals/Humanoid-v0**
This is a trained model of a **SAC** agent playing **seals/Humanoid-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselin... | {"library_name": "stable-baselines3", "tags": ["seals/Humanoid-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "SAC", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/Humanoid-v0", "type": "... | ernestumorga/sac-seals-Humanoid-v0 | null | [
"stable-baselines3",
"seals/Humanoid-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:38:38+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/Humanoid-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# SAC Agent playing seals/Humanoid-v0
This is a trained model of a SAC agent playing seals/Humanoid-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage... | [
"# SAC Agent playing seals/Humanoid-v0\nThis is a trained model of a SAC agent playing seals/Humanoid-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included... | [
"TAGS\n#stable-baselines3 #seals/Humanoid-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# SAC Agent playing seals/Humanoid-v0\nThis is a trained model of a SAC agent playing seals/Humanoid-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training ... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **seals/Swimmer-v0**
This is a trained model of a **PPO** agent playing **seals/Swimmer-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines... | {"library_name": "stable-baselines3", "tags": ["seals/Swimmer-v0", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "seals/Swimmer-v0", "type": "se... | ernestumorga/ppo-seals-Swimmer-v0 | null | [
"stable-baselines3",
"seals/Swimmer-v0",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-11T11:40:57+00:00 | [] | [] | TAGS
#stable-baselines3 #seals/Swimmer-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing seals/Swimmer-v0
This is a trained model of a PPO agent playing seals/Swimmer-v0
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (... | [
"# PPO Agent playing seals/Swimmer-v0\nThis is a trained model of a PPO agent playing seals/Swimmer-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-trained agents included."... | [
"TAGS\n#stable-baselines3 #seals/Swimmer-v0 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing seals/Swimmer-v0\nThis is a trained model of a PPO agent playing seals/Swimmer-v0\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training fra... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-fr_s980
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 (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-fr_s980 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T11:50:21+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-fr_s980
Fine-tuned facebook/wav2vec2-large-fr-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-fr_s980\n\nFine-tuned facebook/wav2vec2-large-fr-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-fr_s980\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition using the train split of Common Voic... |
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-s
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-s", "results": []}]} | paola-md/recipe-roberta-s | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T12:00:58+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| recipe-roberta-s
================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8870
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More informati... | [
"### 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\... |
null | null | Watching YouTube videos too boring for you? Wish you could be punished for not clicking on stuff fast enough while you watch a cat play the piano? Well, LaserTube is here to solve that problem, by letting you turn any YouTube video into a genuine simulation of an oldschool laserdisc arcade game!
Work in progress. | {} | egg22314/LaserTube | null | [
"region:us"
] | null | 2022-07-11T12:01:55+00:00 | [] | [] | TAGS
#region-us
| Watching YouTube videos too boring for you? Wish you could be punished for not clicking on stuff fast enough while you watch a cat play the piano? Well, LaserTube is here to solve that problem, by letting you turn any YouTube video into a genuine simulation of an oldschool laserdisc arcade game!
Work in progress. | [] | [
"TAGS\n#region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-es_s859
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 (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-es_s859 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T12:11:34+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-es_s859
Fine-tuned facebook/wav2vec2-large-es-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-es_s859\n\nFine-tuned facebook/wav2vec2-large-es-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-es_s859\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
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. -->
# finetuned-test-1
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conl... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "model-index": [{"name": "finetuned-test-1", "results": []}]} | ariesutiono/finetuned-test-1 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T12:24:51+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| finetuned-test-1
================
This model is a fine-tuned version of bert-base-uncased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 1.8192
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More... | [
"### 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: 20\n* mixed\\_pre... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #dataset-conll2003 #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\... |
text-generation | transformers |
# Sundrop DialoGPT Model | {"tags": ["conversational"]} | Lamia/DialoGPT-small-Sundrop | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-11T12:32:47+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Sundrop DialoGPT Model | [
"# Sundrop DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Sundrop DialoGPT Model"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-es_s515
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 (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-es_s515 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T12:48:54+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-es_s515
Fine-tuned facebook/wav2vec2-large-es-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-es_s515\n\nFine-tuned facebook/wav2vec2-large-es-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-es_s515\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imdb"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "finetuning-sentiment-model-3000-samples", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "imdb", "type": "imdb", "args": ... | Sahara/finetuning-sentiment-model-3000-samples | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:imdb",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T13:06:19+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-imdb #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3322
- Accuracy: 0.8533
- F1: 0.8562
## Model description
More information needed
## Intended uses & limitations
More in... | [
"# finetuning-sentiment-model-3000-samples\n\nThis model is a fine-tuned version of distilbert-base-uncased on the imdb dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.3322\n- Accuracy: 0.8533\n- F1: 0.8562",
"## Model description\n\nMore information needed",
"## Intended uses & li... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-imdb #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# finetuning-sentiment-model-3000-samples\n\nThis model is a fine-tuned version of distilbert-base-uncased... |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [KD02/distilbert-base-uncased-finetuned-squad](htt... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "distilbert-base-uncased-finetuned-squad", "results": []}]} | KD02/distilbert-base-uncased-finetuned-squad | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T13:14:25+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us
|
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of KD02/distilbert-base-uncased-finetuned-squad on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Tra... | [
"# distilbert-base-uncased-finetuned-squad\n\nThis model is a fine-tuned version of KD02/distilbert-base-uncased-finetuned-squad on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore info... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us \n",
"# distilbert-base-uncased-finetuned-squad\n\nThis model is a fine-tuned version of KD02/distilbert-base-uncased-finetuned-squad on the squad ... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-es_s250
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 (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-es_s250 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T13:22:53+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-es_s250
Fine-tuned facebook/wav2vec2-large-es-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-es_s250\n\nFine-tuned facebook/wav2vec2-large-es-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-es_s250\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-nl_s203
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 (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-nl_s203 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T13:41:38+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-nl_s203
Fine-tuned facebook/wav2vec2-large-nl-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-nl_s203\n\nFine-tuned facebook/wav2vec2-large-nl-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-nl_s203\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-nl_s924
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 (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-nl_s924 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T13:56:23+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-nl_s924
Fine-tuned facebook/wav2vec2-large-nl-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-nl_s924\n\nFine-tuned facebook/wav2vec2-large-nl-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-nl_s924\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-timit-demo-google-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/face... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-timit-demo-google-colab", "results": []}]} | tbboukhari/wav2vec2-base-timit-demo-google-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T13:57:51+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-timit-demo-google-colab
=====================================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5261
* Wer: 0.3351
Model description
-----------------
More information needed
Intend... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 8... |
automatic-speech-recognition | transformers | # exp_w2v2t_es_vp-nl_s878
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 (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-nl_s878 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T14:14:14+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-nl_s878
Fine-tuned facebook/wav2vec2-large-nl-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-nl_s878\n\nFine-tuned facebook/wav2vec2-large-nl-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-nl_s878\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
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. -->
# finetuned-bert-piqa
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the p... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["piqa"], "metrics": ["accuracy"], "model-index": [{"name": "finetuned-bert-piqa", "results": []}]} | sledz08/finetuned-bert-piqa | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"multiple-choice",
"generated_from_trainer",
"dataset:piqa",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T14:23:58+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #dataset-piqa #license-apache-2.0 #endpoints_compatible #region-us
| finetuned-bert-piqa
===================
This model is a fine-tuned version of bert-base-uncased on the piqa dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6603
* Accuracy: 0.6518
Model description
-----------------
More information needed
Intended uses & limitations
--------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 8\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #dataset-piqa #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 8\n* ... |
text2text-generation | generic |
random test repo | {"library_name": "generic", "tags": ["text2text-generation"]} | p-christ/testrepo | null | [
"generic",
"pytorch",
"t5",
"text2text-generation",
"region:us"
] | null | 2022-07-11T14:27:56+00:00 | [] | [] | TAGS
#generic #pytorch #t5 #text2text-generation #region-us
|
random test repo | [] | [
"TAGS\n#generic #pytorch #t5 #text2text-generation #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_es_unispeech-sat_s833
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 spe... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_unispeech-sat_s833 | 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 | 2022-07-11T14:34:36+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_s833
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_s833\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_s833\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
token-classification | transformers | # tner/bert-base-tweetner7-2021
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the
[tner/tweetner7](https://huggingface.co/datasets/tner/tweetner7) dataset (`train_2021` split).
Model fine-tuning is done via [T-NER](https://github.com/asahi417/tner)'s hyper-paramete... | {"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/bert-base-tweetner7-2021 | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T14:41:12+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bert-base-tweetner7-2021
This model is a fine-tuned version of bert-base-cased on the
tner/tweetner7 dataset ('train_2021' 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): 0.606716... | [
"# tner/bert-base-tweetner7-2021\n\nThis model is a fine-tuned version of bert-base-cased on the \ntner/tweetner7 dataset ('train_2021' 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 #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bert-base-tweetner7-2021\n\nThis model is a fine-tuned version of bert-base-cased on the \ntner/tweetner7 dataset ('train_2021' split).\nModel fine-tun... |
token-classification | transformers | # tner/bert-base-tweetner7-all
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) 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 ... | {"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/bert-base-tweetner7-all | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T14:43:31+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bert-base-tweetner7-all
This model is a fine-tuned version of bert-base-cased 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): 0.62302586... | [
"# tner/bert-base-tweetner7-all\n\nThis model is a fine-tuned version of bert-base-cased 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 #bert #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# tner/bert-base-tweetner7-all\n\nThis model is a fine-tuned version of bert-base-cased on the \ntner/tweetner7 dataset ('train_all' split).\nModel fine-tunin... |
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-i
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-i", "results": []}]} | paola-md/recipe-roberta-i | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"generated_from_trainer",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T14:48:05+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #fill-mask #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us
| recipe-roberta-i
================
This model is a fine-tuned version of roberta-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9919
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More informati... | [
"### 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_unispeech-sat_s514
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 spe... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_es_unispeech-sat_s514 | 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 | 2022-07-11T14:56:32+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_s514
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_s514\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_s514\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
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. -->
# bertweet-base-finetuned-emotion
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertwee... | {"tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "bertweet-base-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion", "args": "default"}, "metrics": [... | bhadresh-savani/bertweet-base-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T14:57:26+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-emotion #model-index #autotrain_compatible #endpoints_compatible #region-us
| bertweet-base-finetuned-emotion
===============================
This model is a fine-tuned version of vinai/bertweet-base on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1737
* Accuracy: 0.929
* F1: 0.9296
Model description
-----------------
More information needed
I... | [
"### 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: 4",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-emotion #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* tr... |
token-classification | transformers | # tner/bertweet-base-tweetner7-random
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) 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/tner)'... | {"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-base-tweetner7-random | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-11T15:04:58+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #dataset-tner/tweetner7 #model-index #autotrain_compatible #endpoints_compatible #region-us
| # tner/bertweet-base-tweetner7-random
This model is a fine-tuned version of vinai/bertweet-base 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 (micr... | [
"# tner/bertweet-base-tweetner7-random\n\nThis model is a fine-tuned version of vinai/bertweet-base 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-base-tweetner7-random\n\nThis model is a fine-tuned version of vinai/bertweet-base on the \ntner/tweetner7 dataset ('train_random' split).\... |
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