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automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-es_s952
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-es_s952 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T06:36:29+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-es_s952
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-es_s952\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-es_s952\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of ... |
text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuned-mbart-large-10epoch
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/... | {"language": ["en", "ro"], "tags": ["generated_from_trainer"], "datasets": ["wmt16"], "model-index": [{"name": "finetuned-mbart-large-10epoch", "results": []}]} | Lvxue/finetuned-mbart-large-10epoch | null | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"generated_from_trainer",
"en",
"ro",
"dataset:wmt16",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T06:40:58+00:00 | [] | [
"en",
"ro"
] | TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #autotrain_compatible #endpoints_compatible #region-us
|
# finetuned-mbart-large-10epoch
This model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and... | [
"# finetuned-mbart-large-10epoch\n\nThis model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 2.6032",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information neede... | [
"TAGS\n#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #autotrain_compatible #endpoints_compatible #region-us \n",
"# finetuned-mbart-large-10epoch\n\nThis model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.\nIt achieves the fol... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-es_s474
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-es_s474 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T06:44:40+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-es_s474
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-es_s474\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-es_s474\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of ... |
translation | transformers |
# en-toki-mt
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ROMANCE](https://huggingface.co/Helsinki-NLP/opus-mt-en-ROMANCE) on the English - toki pona translation dataset on Tatoeba.
## Model description
toki pona is a minimalist constructed language created in 2014 by Sonja Lang. The language fea... | {"language": ["en", "tok", "multilingual"], "license": "apache-2.0", "tags": ["generated_from_trainer", "translation"], "widget": [{"text": "Hello, my name is Tom."}, {"text": "Can the cat speak English?"}], "model-index": [{"name": "en-toki-mt", "results": []}]} | ckb/en-toki-mt | null | [
"transformers",
"pytorch",
"safetensors",
"marian",
"text2text-generation",
"generated_from_trainer",
"translation",
"en",
"tok",
"multilingual",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T06:51:22+00:00 | [] | [
"en",
"tok",
"multilingual"
] | TAGS
#transformers #pytorch #safetensors #marian #text2text-generation #generated_from_trainer #translation #en #tok #multilingual #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# en-toki-mt
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ROMANCE on the English - toki pona translation dataset on Tatoeba.
## Model description
toki pona is a minimalist constructed language created in 2014 by Sonja Lang. The language features a very small volcabulary (~130 words) and a very sim... | [
"# en-toki-mt\n\nThis model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ROMANCE on the English - toki pona translation dataset on Tatoeba.",
"## Model description\n\ntoki pona is a minimalist constructed language created in 2014 by Sonja Lang. The language features a very small volcabulary (~130 words) an... | [
"TAGS\n#transformers #pytorch #safetensors #marian #text2text-generation #generated_from_trainer #translation #en #tok #multilingual #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# en-toki-mt\n\nThis model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ROMANCE on the English... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-es_s186
Fine-tuned [facebook/wav2vec2-large-es-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-es-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-es_s186 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T06:53:28+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-es_s186
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-es_s186\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-es_s186\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition on English using the train split of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-nl_s169
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-nl_s169 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T06:59:51+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-nl_s169
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-nl_s169\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-nl_s169\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-nl_s281
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-nl_s281 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:08:43+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-nl_s281
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-nl_s281\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-nl_s281\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-nl_s980
Fine-tuned [facebook/wav2vec2-large-nl-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-nl-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-nl_s980 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:16:42+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-nl_s980
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-nl_s980\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-nl_s980\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition on English using the train split of ... |
feature-extraction | transformers |
# Legal BERT model applicable for Dutch and English
A BERT model further trained from [mBERT](https://huggingface.co/bert-base-multilingual-uncased) on legal documents. The thesis can be downloaded [here](https://www.ru.nl/publish/pages/769526/gerwin_de_kruijf.pdf).
## Data
The model is further trained the same way a... | {"language": ["en", "nl"], "license": "apache-2.0", "tags": ["bert", "legal", "multilingual"], "metrics": ["F1"]} | Gerwin/legal-bert-dutch-english | null | [
"transformers",
"pytorch",
"tf",
"bert",
"feature-extraction",
"legal",
"multilingual",
"en",
"nl",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:21:25+00:00 | [] | [
"en",
"nl"
] | TAGS
#transformers #pytorch #tf #bert #feature-extraction #legal #multilingual #en #nl #license-apache-2.0 #endpoints_compatible #region-us
| Legal BERT model applicable for Dutch and English
=================================================
A BERT model further trained from mBERT on legal documents. The thesis can be downloaded here.
Data
----
The model is further trained the same way as EurlexBERT: regulations, decisions, directives, and parliamentar... | [
"### Legal topic classification",
"### Multi-class classification (Rabobank)\n\n\nThis dataset is not open-source, but it is still an interesting case since the dataset contains both Dutch and English legal documents that have to be classified. The dataset consists of 8000 long legal documents (2000 Dutch & 6000 ... | [
"TAGS\n#transformers #pytorch #tf #bert #feature-extraction #legal #multilingual #en #nl #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Legal topic classification",
"### Multi-class classification (Rabobank)\n\n\nThis dataset is not open-source, but it is still an interesting case since the data... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_unispeech-sat_s456
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_unispeech-sat_s456 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:26:01+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_unispeech-sat_s456
Fine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0.
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_en_unispeech-sat_s456\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_unispeech-sat_s456\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train spl... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_unispeech-sat_s251
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_unispeech-sat_s251 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:36:07+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_unispeech-sat_s251
Fine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0.
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_en_unispeech-sat_s251\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_unispeech-sat_s251\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train spl... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_unispeech-sat_s459
Fine-tuned [microsoft/unispeech-sat-large](https://huggingface.co/microsoft/unispeech-sat-large) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:46:09+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_unispeech-sat_s459
Fine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0.
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_en_unispeech-sat_s459\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_unispeech-sat_s459\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train spl... |
text-generation | transformers |
#Michael from Office DialoGPT Model | {"tags": ["conversational"]} | SafeTorpedo/DialoGPT-small-MichaelBot | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-08T07:50:41+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
#Michael from Office DialoGPT Model | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_en_xls-r_s957
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_xls-r_s957 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T07:54:25+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_xls-r_s957
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common Voice 7.0.
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_en_xls-r_s957\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_xls-r_s957\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_xls-r_s732
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_xls-r_s732 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:02:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_xls-r_s732
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common Voice 7.0.
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_en_xls-r_s732\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_xls-r_s732\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common V... |
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": ... | rahuldebdas79/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 | 2022-07-08T08:05:15+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: 0.3157
- Accuracy: 0.8667
- F1: 0.8684
## 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: 0.3157\n- Accuracy: 0.8667\n- F1: 0.8684",
"## 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... |
feature-extraction | transformers |
# ERNIE-Gram-chinese
## Introduction
ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding
More detail: https://arxiv.org/abs/2010.12148
## Released Model Info
|Model Name|Language|Model Structure|
|:---:|:---:|:---:|
|ernie-gram-chinese| Chinese |Layer:12, Hi... | {"language": "chinese"} | swtx/ernie-gram-chinese | null | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"arxiv:2010.12148",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:09:46+00:00 | [
"2010.12148"
] | [
"chinese"
] | TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2010.12148 #endpoints_compatible #region-us
| ERNIE-Gram-chinese
==================
Introduction
------------
ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding
More detail: URL
Released Model Info
-------------------
This released Pytorch model is converted from the officially released PaddlePadd... | [] | [
"TAGS\n#transformers #pytorch #bert #feature-extraction #arxiv-2010.12148 #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_en_xls-r_s468
Fine-tuned [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_xls-r_s468 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:10:00+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_xls-r_s468
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common Voice 7.0.
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_en_xls-r_s468\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_xls-r_s468\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition on English using the train split of Common V... |
feature-extraction | transformers | ## swtx SIMCSE RoBERTa WWM Ext Chinese
This model provides simplified Chinese sentence embeddings encoding based on [Simple Contrastive Learning](https://arxiv.org/abs/2104.08821).
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding.
## How to use
```Python
from transformers import AutoTokenize... | {} | swtx/simcse-chinese-roberta-www-ext | null | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"arxiv:2104.08821",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:13:31+00:00 | [
"2104.08821"
] | [] | TAGS
#transformers #pytorch #bert #feature-extraction #arxiv-2104.08821 #endpoints_compatible #region-us
| ## swtx SIMCSE RoBERTa WWM Ext Chinese
This model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.
The pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding.
## How to use
| [
"## swtx SIMCSE RoBERTa WWM Ext Chinese\n\nThis model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.\nThe pretrained model(Chinese RoBERTa WWM Ext) is used for token encoding.",
"## How to use"
] | [
"TAGS\n#transformers #pytorch #bert #feature-extraction #arxiv-2104.08821 #endpoints_compatible #region-us \n",
"## swtx SIMCSE RoBERTa WWM Ext Chinese\n\nThis model provides simplified Chinese sentence embeddings encoding based on Simple Contrastive Learning.\nThe pretrained model(Chinese RoBERTa WWM Ext) is use... |
null | transformers |
# ERNIE 3.0 轻量级模型
**目录**
* [模型介绍](#模型介绍)
* [在线蒸馏技术](#在线蒸馏技术)
* [模型效果](#模型效果)
* [微调](#微调)
* [模型压缩](#模型压缩)
* [环境依赖](#环境依赖)
* [模型压缩 API 使用](#模型压缩API使用)
* [压缩效果](#压缩效果)
* [精度测试](#精度测试)
* [性能测试](#性能测试)
* [CPU 性能](#CPU性能)
* [GPU 性能... | {"license": "apache-2.0"} | swtx/ernie-3.0-base-chinese | null | [
"transformers",
"pytorch",
"arxiv:2106.02241",
"arxiv:2112.12731",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:14:51+00:00 | [
"2106.02241",
"2112.12731"
] | [] | TAGS
#transformers #pytorch #arxiv-2106.02241 #arxiv-2112.12731 #license-apache-2.0 #endpoints_compatible #region-us
| ERNIE 3.0 轻量级模型
===============
目录
* 模型介绍
+ 在线蒸馏技术
* 模型效果
* 微调
* 模型压缩
+ 环境依赖
+ 模型压缩 API 使用
+ 压缩效果
- 精度测试
- 性能测试
* CPU 性能
* GPU 性能
* 使用 FasterTokenizer 加速
* 部署
+ Python 部署
+ 服务化部署
+ Paddle2ONNX 部署
* Notebook教程
* 参考文献
模型介绍
----
本次开源的模型是在文心大模型ERNIE 3.0 基础上通过在线蒸馏技术得到的轻量级模型，模型结构与 ERNIE 2.0 保持一致，相比 ... | [
"### 在线蒸馏技术\n\n\n在线蒸馏技术在模型学习的过程中周期性地将知识信号传递给若干个学生模型同时训练，从而在蒸馏阶段一次性产出多种尺寸的学生模型。相对传统蒸馏技术，该技术极大节省了因大模型额外蒸馏计算以及多个学生的重复知识传递带来的算力消耗。\n\n\n这种新颖的蒸馏方式利用了文心大模型的规模优势，在蒸馏完成后保证了学生模型的效果和尺寸丰富性，方便不同性能需求的应用场景使用。此外，由于文心大模型的模型尺寸与学生模型差距巨大，模型蒸馏难度极大甚至容易失效。为此，通过引入了助教模型进行蒸馏的技术，利用助教作为知识传递的桥梁以缩短学生模型和大模型表达空间相距过大的问题，从而促进蒸馏效率的提升。\n\n\n更多技术细节可以... | [
"TAGS\n#transformers #pytorch #arxiv-2106.02241 #arxiv-2112.12731 #license-apache-2.0 #endpoints_compatible #region-us \n",
"### 在线蒸馏技术\n\n\n在线蒸馏技术在模型学习的过程中周期性地将知识信号传递给若干个学生模型同时训练，从而在蒸馏阶段一次性产出多种尺寸的学生模型。相对传统蒸馏技术，该技术极大节省了因大模型额外蒸馏计算以及多个学生的重复知识传递带来的算力消耗。\n\n\n这种新颖的蒸馏方式利用了文心大模型的规模优势，在蒸馏完成后保证了学生模型的效果和尺寸丰富性，方便不同性能需求的应用场... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_r-wav2vec2_s863
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s863 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:18:31+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_r-wav2vec2_s863
Fine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Common Voice 7.0.
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_en_r-wav2vec2_s863\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_r-wav2vec2_s863\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of C... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comple... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | epsil/testpyramidsrnd | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2022-07-08T08:27:16+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the trainin... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the t... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documen... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_r-wav2vec2_s93
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s93 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:28:09+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_r-wav2vec2_s93
Fine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Common Voice 7.0.
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_en_r-wav2vec2_s93\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_r-wav2vec2_s93\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Co... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1540882647232266249/rccH... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "http://www.huggingtweets.com/markzero/1657272867878/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/markzero | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-08T08:32:32+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
mark zero dot earth
@markzero
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
---... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers | # exp_w2v2t_en_r-wav2vec2_s44
Fine-tuned [facebook/wav2vec2-large-robust](https://huggingface.co/facebook/wav2vec2-large-robust) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_r-wav2vec2_s44 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:35:33+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_r-wav2vec2_s44
Fine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Common Voice 7.0.
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_en_r-wav2vec2_s44\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_r-wav2vec2_s44\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition on English using the train split of Co... |
translation | transformers |
# NLLB-200
This is the model card of NLLB-200's distilled 600M variant.
Here are the [metrics](https://tinyurl.com/nllb200densedst600mmetrics) for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algor... | {"language": ["ace", "acm", "acq", "aeb", "af", "ajp", "ak", "als", "am", "apc", "ar", "ars", "ary", "arz", "as", "ast", "awa", "ayr", "azb", "azj", "ba", "bm", "ban", "be", "bem", "bn", "bho", "bjn", "bo", "bs", "bug", "bg", "ca", "ceb", "cs", "cjk", "ckb", "crh", "cy", "da", "de", "dik", "dyu", "dz", "el", "en", "eo"... | facebook/nllb-200-distilled-600M | null | [
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# NLLB-200
This is the model card of NLLB-200's distilled 600M variant.
Here are the metrics for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbal... | [
"# NLLB-200\n\nThis is the model card of NLLB-200's distilled 600M variant.\n\nHere are the metrics for that particular checkpoint.\n\n- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle ... | [
"TAGS\n#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #f... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-it_s859
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-it_s859 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:51:29+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-it_s859
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-it_s859\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-it_s859\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of ... |
text2text-generation | transformers | ## m2m100 fine-tuned on Softcatalà's parallel Catalan-German dataset for machine translation
## Table of Contents
<details>
<summary>Click to expand</summary>
- [Model description](#model-description)
- [Intended uses and limitations](#intended-use)
- [How to Use](#how-to-use)
- [Training](#training)
- [Training d... | {"language": ["ca", "de", "multilingual"], "license": "cc-by-4.0", "datasets": ["Softcatala/parallel-catalan-corpus/deu-cat"], "metrics": ["bleu", "meteor", "chrf", "ter"], "model-index": [{"name": "m2m100_418M_ft_de_ca", "results": [{"task": {"type": "translation"}, "dataset": {"name": "Flores", "type": "flores"}, "me... | projecte-aina/m2m100-418M-ft-de-ca | null | [
"transformers",
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"m2m_100",
"text2text-generation",
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"de",
"multilingual",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-07-08T08:51:44+00:00 | [] | [
"ca",
"de",
"multilingual"
] | TAGS
#transformers #pytorch #m2m_100 #text2text-generation #ca #de #multilingual #license-cc-by-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
| m2m100 fine-tuned on Softcatalà's parallel Catalan-German dataset for machine translation
-----------------------------------------------------------------------------------------
Table of Contents
-----------------
Click to expand
* Model description
* Intended uses and limitations
* How to Use
* Training
+ Trai... | [
"### Training data\n\n\nAs a data for fine-tuning we used the Softcatalà Catalan-German parallel corpus dataset, with sentences deduplicated and filtered by the GEnCaTa quality filter.",
"### Training procedure",
"#### Tokenization\n\n\nThe original m2m100\\_418M model's sentencepiece tokenizer was used.",
"#... | [
"TAGS\n#transformers #pytorch #m2m_100 #text2text-generation #ca #de #multilingual #license-cc-by-4.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### Training data\n\n\nAs a data for fine-tuning we used the Softcatalà Catalan-German parallel corpus dataset, with sentences ... |
fill-mask | transformers | ## RoBERTa Latin model, version 2 --> model card not finished yet
This is a Latin RoBERTa-based LM model, version 2.
The intention of the Transformer-based LM is twofold: on the one hand, it will be used for the evaluation of HTR results; on the other, it should be used as a decoder for the TrOCR architecture.
The t... | {} | pstroe/roberta-base-latin-cased2 | null | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"arxiv:2009.10053",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:54:32+00:00 | [
"2009.10053"
] | [] | TAGS
#transformers #pytorch #roberta #fill-mask #arxiv-2009.10053 #autotrain_compatible #endpoints_compatible #region-us
| ## RoBERTa Latin model, version 2 --> model card not finished yet
This is a Latin RoBERTa-based LM model, version 2.
The intention of the Transformer-based LM is twofold: on the one hand, it will be used for the evaluation of HTR results; on the other, it should be used as a decoder for the TrOCR architecture.
The t... | [
"## RoBERTa Latin model, version 2 --> model card not finished yet\n\nThis is a Latin RoBERTa-based LM model, version 2.\n\nThe intention of the Transformer-based LM is twofold: on the one hand, it will be used for the evaluation of HTR results; on the other, it should be used as a decoder for the TrOCR architectur... | [
"TAGS\n#transformers #pytorch #roberta #fill-mask #arxiv-2009.10053 #autotrain_compatible #endpoints_compatible #region-us \n",
"## RoBERTa Latin model, version 2 --> model card not finished yet\n\nThis is a Latin RoBERTa-based LM model, version 2.\n\nThe intention of the Transformer-based LM is twofold: on the o... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-it_s515
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-it_s515 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T08:57:51+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-it_s515
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-it_s515\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-it_s515\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_en_vp-it_s250
Fine-tuned [facebook/wav2vec2-large-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-it-voxpopuli) for speech recognition on English using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure t... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_en_vp-it_s250 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:02:46+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_en_vp-it_s250
Fine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.
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_en_vp-it_s250\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of Common Voice 7.0.\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 #en #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_en_vp-it_s250\n\nFine-tuned facebook/wav2vec2-large-it-voxpopuli for speech recognition on English using the train split of ... |
translation | transformers |
# NLLB-200
This is the model card of NLLB-200's 3.3B variant.
Here are the [metrics](https://tinyurl.com/nllb200dense3bmetrics) for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and ... | {"language": ["ace", "acm", "acq", "aeb", "af", "ajp", "ak", "als", "am", "apc", "ar", "ars", "ary", "arz", "as", "ast", "awa", "ayr", "azb", "azj", "ba", "bm", "ban", "be", "bem", "bn", "bho", "bjn", "bo", "bs", "bug", "bg", "ca", "ceb", "cs", "cjk", "ckb", "crh", "cy", "da", "de", "dik", "dyu", "dz", "el", "en", "eo"... | facebook/nllb-200-3.3B | null | [
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"ceb",
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"cjk",
"ckb",... | TAGS
#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #fi #fon... |
# NLLB-200
This is the model card of NLLB-200's 3.3B variant.
Here are the metrics for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbalances for ... | [
"# NLLB-200\n\nThis is the model card of NLLB-200's 3.3B variant.\n\nHere are the metrics for that particular checkpoint.\n\n- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbal... | [
"TAGS\n#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #f... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_wav2vec2_s664
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_wav2vec2_s664 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:06:28+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_wav2vec2_s664
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_wav2vec2_s664\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_wav2vec2_s664\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_wav2vec2_s729
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_wav2vec2_s729 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:10:37+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_wav2vec2_s729
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_wav2vec2_s729\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_wav2vec2_s729\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common V... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_wav2vec2_s35
Fine-tuned [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech i... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_wav2vec2_s35 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:13:35+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_wav2vec2_s35
Fine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_wav2vec2_s35\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_wav2vec2_s35\n\nFine-tuned facebook/wav2vec2-large-lv60 for speech recognition on Thai using the train split of Common Vo... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-100k_s403
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sur... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-100k_s403 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:17:54+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-100k_s403
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-100k_s403\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-100k_s403\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-100k_s497
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sur... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-100k_s497 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:20:58+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-100k_s497
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-100k_s497\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-100k_s497\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-100k_s630
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sur... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-100k_s630 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:23:54+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-100k_s630
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-100k_s630\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-100k_s630\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli for speech recognition on Thai using the train split of... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_xlsr-53_s711
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your sp... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_xlsr-53_s711 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:26:54+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_xlsr-53_s711
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_xlsr-53_s711\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_xlsr-53_s711\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_xlsr-53_s201
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your sp... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_xlsr-53_s201 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:30:49+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_xlsr-53_s201
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_xlsr-53_s201\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_xlsr-53_s201\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_xlsr-53_s218
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your sp... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_xlsr-53_s218 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:34:50+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_xlsr-53_s218
Fine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_xlsr-53_s218\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_xlsr-53_s218\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 for speech recognition on Thai using the train split of Common... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech_s328
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech_s328 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:38:31+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech_s328
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_unispeech_s328\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech_s328\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech_s624
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech_s624 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:41:56+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech_s624
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_unispeech_s624\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech_s624\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of ... |
translation | transformers |
# NLLB-200
This is the model card of NLLB-200's 1.3B variant.
Here are the [metrics](https://tinyurl.com/nllb200dense1bmetrics) for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and ... | {"language": ["ace", "acm", "acq", "aeb", "af", "ajp", "ak", "als", "am", "apc", "ar", "ars", "ary", "arz", "as", "ast", "awa", "ayr", "azb", "azj", "ba", "bm", "ban", "be", "bem", "bn", "bho", "bjn", "bo", "bs", "bug", "bg", "ca", "ceb", "cs", "cjk", "ckb", "crh", "cy", "da", "de", "dik", "dyu", "dz", "el", "en", "eo"... | facebook/nllb-200-1.3B | null | [
"transformers",
"pytorch",
"m2m_100",
"text2text-generation",
"nllb",
"translation",
"ace",
"acm",
"acq",
"aeb",
"af",
"ajp",
"ak",
"als",
"am",
"apc",
"ar",
"ars",
"ary",
"arz",
"as",
"ast",
"awa",
"ayr",
"azb",
"azj",
"ba",
"bm",
"ban",
"be",
"bem",
"b... | null | 2022-07-08T09:42:11+00:00 | [] | [
"ace",
"acm",
"acq",
"aeb",
"af",
"ajp",
"ak",
"als",
"am",
"apc",
"ar",
"ars",
"ary",
"arz",
"as",
"ast",
"awa",
"ayr",
"azb",
"azj",
"ba",
"bm",
"ban",
"be",
"bem",
"bn",
"bho",
"bjn",
"bo",
"bs",
"bug",
"bg",
"ca",
"ceb",
"cs",
"cjk",
"ckb",... | TAGS
#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #fi #fon... |
# NLLB-200
This is the model card of NLLB-200's 1.3B variant.
Here are the metrics for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbalances for ... | [
"# NLLB-200\n\nThis is the model card of NLLB-200's 1.3B variant.\n\nHere are the metrics for that particular checkpoint.\n\n- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbal... | [
"TAGS\n#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #f... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech_s131
Fine-tuned [microsoft/unispeech-large-1500h-cv](https://huggingface.co/microsoft/unispeech-large-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech_s131 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:45:06+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech_s131
Fine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_unispeech_s131\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech_s131\n\nFine-tuned microsoft/unispeech-large-1500h-cv for speech recognition on Thai using the train split of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_hubert_s975
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inpu... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_hubert_s975 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:48:19+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_hubert_s975
Fine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_hubert_s975\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_hubert_s975\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice ... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_hubert_s533
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inpu... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_hubert_s533 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:51:52+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_hubert_s533
Fine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_hubert_s533\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_hubert_s533\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice ... |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner_swedish_small_set_health_and_prices
This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner]... | {"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ner_swedish_small_set_health_and_prices", "results": []}]} | Nonzerophilip/bert-finetuned-ner_swedish_small_set_health_and_prices | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:53:18+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us
| bert-finetuned-ner\_swedish\_small\_set\_health\_and\_prices
============================================================
This model is a fine-tuned version of KBLab/bert-base-swedish-cased-ner on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0942
* Precision: 0.7709
* Recall:... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #token-classification #generated_from_trainer #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: 8\n* eval\\_... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_hubert_s817
Fine-tuned [facebook/hubert-large-ll60k](https://huggingface.co/facebook/hubert-large-ll60k) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech inpu... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_hubert_s817 | null | [
"transformers",
"pytorch",
"hubert",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:54:47+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #hubert #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_hubert_s817
Fine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_hubert_s817\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_hubert_s817\n\nFine-tuned facebook/hubert-large-ll60k for speech recognition on Thai using the train split of Common Voice ... |
translation | transformers |
# NLLB-200
This is the model card of NLLB-200's distilled 1.3B variant.
Here are the [metrics](https://tinyurl.com/nllb200densedst1bmetrics) for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorit... | {"language": ["ace", "acm", "acq", "aeb", "af", "ajp", "ak", "als", "am", "apc", "ar", "ars", "ary", "arz", "as", "ast", "awa", "ayr", "azb", "azj", "ba", "bm", "ban", "be", "bem", "bn", "bho", "bjn", "bo", "bs", "bug", "bg", "ca", "ceb", "cs", "cjk", "ckb", "crh", "cy", "da", "de", "dik", "dyu", "dz", "el", "en", "eo"... | facebook/nllb-200-distilled-1.3B | null | [
"transformers",
"pytorch",
"m2m_100",
"text2text-generation",
"nllb",
"translation",
"ace",
"acm",
"acq",
"aeb",
"af",
"ajp",
"ak",
"als",
"am",
"apc",
"ar",
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"ary",
"arz",
"as",
"ast",
"awa",
"ayr",
"azb",
"azj",
"ba",
"bm",
"ban",
"be",
"bem",
"b... | null | 2022-07-08T09:57:38+00:00 | [] | [
"ace",
"acm",
"acq",
"aeb",
"af",
"ajp",
"ak",
"als",
"am",
"apc",
"ar",
"ars",
"ary",
"arz",
"as",
"ast",
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"ayr",
"azb",
"azj",
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"ban",
"be",
"bem",
"bn",
"bho",
"bjn",
"bo",
"bs",
"bug",
"bg",
"ca",
"ceb",
"cs",
"cjk",
"ckb",... | TAGS
#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #fi #fon... |
# NLLB-200
This is the model card of NLLB-200's distilled 1.3B variant.
Here are the metrics for that particular checkpoint.
- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbal... | [
"# NLLB-200\n\nThis is the model card of NLLB-200's distilled 1.3B variant.\n\nHere are the metrics for that particular checkpoint.\n\n- Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle ... | [
"TAGS\n#transformers #pytorch #m2m_100 #text2text-generation #nllb #translation #ace #acm #acq #aeb #af #ajp #ak #als #am #apc #ar #ars #ary #arz #as #ast #awa #ayr #azb #azj #ba #bm #ban #be #bem #bn #bho #bjn #bo #bs #bug #bg #ca #ceb #cs #cjk #ckb #crh #cy #da #de #dik #dyu #dz #el #en #eo #et #eu #ee #fo #fj #f... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-sv_s946
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-sv_s946 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T09:57:48+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-sv_s946
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-sv_s946\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-sv_s946\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Com... |
reinforcement-learning | stable-baselines3 |
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framewor... | {"library_name": "stable-baselines3", "tags": ["SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "DQN", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "SpaceInvadersNoFram... | Lakshya/dqn-SpaceInvadersNoFrameskip-v4 | null | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-08T09:59:03+00:00 | [] | [] | TAGS
#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4
using the stable-baselines3 library
and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents... | [
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo.\n\nThe RL Zoo is a training framework for Stable Baselines3\nreinforcement learning agents,\nwith hyperparameter optimization and pre-tra... | [
"TAGS\n#stable-baselines3 #SpaceInvadersNoFrameskip-v4 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# DQN Agent playing SpaceInvadersNoFrameskip-v4\nThis is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4\nusing the stable-baselines3 library\nand the RL Zoo... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-sv_s635
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-sv_s635 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:00:49+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-sv_s635
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-sv_s635\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-sv_s635\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Com... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-sv_s884
Fine-tuned [facebook/wav2vec2-large-sv-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-sv_s884 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:03:49+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-sv_s884
Fine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-sv_s884\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-sv_s884\n\nFine-tuned facebook/wav2vec2-large-sv-voxpopuli for speech recognition on Thai using the train split of Com... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_no-pretraining_s950
Fine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of [Common Voice 7.0](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... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_no-pretraining_s950 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:06:50+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_no-pretraining_s950
Fine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_no-pretraining_s950\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_no-pretraining_s950\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train spli... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_no-pretraining_s414
Fine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of [Common Voice 7.0](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... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_no-pretraining_s414 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:10:08+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_no-pretraining_s414
Fine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_no-pretraining_s414\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_no-pretraining_s414\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train spli... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_no-pretraining_s156
Fine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of [Common Voice 7.0](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... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_no-pretraining_s156 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:13:24+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_no-pretraining_s156
Fine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_no-pretraining_s156\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_no-pretraining_s156\n\nFine-tuned randomly initialized wav2vec2 model for speech recognition on Thai using the train spli... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_wavlm_s108
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_wavlm_s108 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:16:18+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_wavlm_s108
Fine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_wavlm_s108\n\nFine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_wavlm_s108\n\nFine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.\nWh... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_wavlm_s847
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_wavlm_s847 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:20:15+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_wavlm_s847
Fine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_wavlm_s847\n\nFine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_wavlm_s847\n\nFine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.\nWh... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_wavlm_s904
Fine-tuned [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input is sampled ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_wavlm_s904 | null | [
"transformers",
"pytorch",
"wavlm",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:23:56+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wavlm #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_wavlm_s904
Fine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_wavlm_s904\n\nFine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_wavlm_s904\n\nFine-tuned microsoft/wavlm-large for speech recognition on Thai using the train split of Common Voice 7.0.\nWh... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech-ml_s256
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When u... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech-ml_s256 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:27:41+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech-ml_s256
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_unispeech-ml_s256\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech-ml_s256\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using th... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech-ml_s640
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When u... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech-ml_s640 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:30:45+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech-ml_s640
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_unispeech-ml_s640\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech-ml_s640\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using th... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech-ml_s351
Fine-tuned [microsoft/unispeech-large-multi-lingual-1500h-cv](https://huggingface.co/microsoft/unispeech-large-multi-lingual-1500h-cv) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When u... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech-ml_s351 | null | [
"transformers",
"pytorch",
"unispeech",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:33:47+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech-ml_s351
Fine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_unispeech-ml_s351\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech-ml_s351\n\nFine-tuned microsoft/unispeech-large-multi-lingual-1500h-cv for speech recognition on Thai using th... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-fr_s761
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-fr_s761 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:37:06+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-fr_s761
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-fr_s761\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-fr_s761\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Com... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-fr_s77
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-fr_s77 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:40:05+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-fr_s77
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-fr_s77\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-fr_s77\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Comm... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-fr_s22
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) for speech recognition on Thai using the train split of [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-fr_s22 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:43:19+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-fr_s22
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.
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_th_vp-fr_s22\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Common Voice 7.0.\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-fr_s22\n\nFine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai using the train split of Comm... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-ft650_6class
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingfa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-ft650_6class", "results": []}]} | dminiotas05/distilbert-base-uncased-finetuned-ft650_6class | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T10:46:36+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-ft650\_6class
===============================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4555
* Accuracy: 0.3707
* F1: 0.3625
Model description
-----------... | [
"### 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 #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_b... |
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. -->
# deberta-v3-xsmall-with-biblio-context-frozenlm-finetuned-review_classifier
This model is a fine-tuned version of [microsoft/debe... | {"license": "mit", "tags": ["text-classification", "generated_from_trainer"], "metrics": ["accuracy", "f1", "recall", "precision"], "model-index": [{"name": "deberta-v3-xsmall-with-biblio-context-frozenlm-finetuned-review_classifier", "results": []}]} | domenicrosati/deberta-v3-xsmall-with-biblio-context-frozenlm-finetuned-review_classifier | null | [
"transformers",
"pytorch",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T11:06:35+00:00 | [] | [] | TAGS
#transformers #pytorch #deberta-v2 #text-classification #generated_from_trainer #license-mit #endpoints_compatible #region-us
| deberta-v3-xsmall-with-biblio-context-frozenlm-finetuned-review\_classifier
===========================================================================
This model is a fine-tuned version of microsoft/deberta-v3-xsmall on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3109
* A... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 4.5e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\_size: 12\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\\_ste... | [
"TAGS\n#transformers #pytorch #deberta-v2 #text-classification #generated_from_trainer #license-mit #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 4.5e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\_size: ... |
reinforcement-learning | ml-agents |
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started
We wrote a comple... | {"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids"]} | ramonzaca/testpyramidsrnd | null | [
"ml-agents",
"tensorboard",
"onnx",
"unity-ml-agents",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | null | 2022-07-08T11:16:09+00:00 | [] | [] | TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us
|
# ppo Agent playing Pyramids
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
## Usage (with ML-Agents)
The Documentation: URL
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
### Resume the trainin... | [
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documentation: URL\n We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:\n\n\n ### Resume the t... | [
"TAGS\n#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Pyramids #region-us \n",
"# ppo Agent playing Pyramids\n This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.\n \n ## Usage (with ML-Agents)\n The Documen... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-es_s26
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-es_s26 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T11:25:24+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-es_s26
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).
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_th_vp-es_s26\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-es_s26\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli 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... | maurya/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-08T11:53:01+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing LunarLander-v2\nThis is a trained model of a PPO agent playing LunarLander-v2\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add you... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```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... | LongquanJiang/LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-08T11:56:34+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
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... |
text-classification | transformers |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1105140277
- CO2 Emissions (in grams): 0.1863935648335355
## Validation Metrics
- Loss: 0.0680043175816536
- Accuracy: 0.9808
- Macro F1: 0.9808013970263609
- Micro F1: 0.9808
- Weighted F1: 0.9808013970263609
- Macro Precision: ... | {"language": "unk", "tags": "autotrain", "datasets": ["jk-gjom/autotrain-data-jk123"], "widget": [{"text": "I love AutoTrain \ud83e\udd17"}], "co2_eq_emissions": 0.1863935648335355} | jk-gjom/autotrain-jk123-1105140277 | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autotrain",
"unk",
"dataset:jk-gjom/autotrain-data-jk123",
"co2_eq_emissions",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T11:59:42+00:00 | [] | [
"unk"
] | TAGS
#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-jk-gjom/autotrain-data-jk123 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us
|
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1105140277
- CO2 Emissions (in grams): 0.1863935648335355
## Validation Metrics
- Loss: 0.0680043175816536
- Accuracy: 0.9808
- Macro F1: 0.9808013970263609
- Micro F1: 0.9808
- Weighted F1: 0.9808013970263609
- Macro Precision: ... | [
"# Model Trained Using AutoTrain\n\n- Problem type: Multi-class Classification\n- Model ID: 1105140277\n- CO2 Emissions (in grams): 0.1863935648335355",
"## Validation Metrics\n\n- Loss: 0.0680043175816536\n- Accuracy: 0.9808\n- Macro F1: 0.9808013970263609\n- Micro F1: 0.9808\n- Weighted F1: 0.9808013970263609\n... | [
"TAGS\n#transformers #pytorch #bert #text-classification #autotrain #unk #dataset-jk-gjom/autotrain-data-jk123 #co2_eq_emissions #autotrain_compatible #endpoints_compatible #region-us \n",
"# Model Trained Using AutoTrain\n\n- Problem type: Multi-class Classification\n- Model ID: 1105140277\n- CO2 Emissions (in g... |
reinforcement-learning | null |
# **Reinforce** Agent playing **CartPole-v1**
This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
| {"tags": ["CartPole-v1", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-cartpole_v1", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "CartPole-v1", "type": "CartPole-v1"}, "metrics": [{... | Guillaume63/Reinforce-cartpole_v1 | null | [
"CartPole-v1",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2022-07-08T12:10:02+00:00 | [] | [] | TAGS
#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing CartPole-v1
This is a trained model of a Reinforce agent playing CartPole-v1 .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL
| [
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL"
] | [
"TAGS\n#CartPole-v1 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing CartPole-v1\n This is a trained model of a Reinforce agent playing CartPole-v1 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcemen... |
text-generation | transformers |
# German Covid-19 GPT2-XL (1.5B)
- Covid-19 specific version of [`malteos/gpt2-xl-wechsel-german`](https://huggingface.co/malteos/gpt2-xl-wechsel-german)
- Fine-tuned on 2 GB text from OSCAR filtered for covid related terms.
### How to use
You can use this model directly with a pipeline for text generation. Since... | {"language": "de", "license": "mit", "widget": [{"text": "Noch Wochen nach einer Erkrankung an COVID-19 k\u00f6nnen "}]} | malteos/gpt2-xl-german-covid-19 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-08T12:14:23+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #de #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# German Covid-19 GPT2-XL (1.5B)
- Covid-19 specific version of 'malteos/gpt2-xl-wechsel-german'
- Fine-tuned on 2 GB text from OSCAR filtered for covid related terms.
### How to use
You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we
set a seed ... | [
"# German Covid-19 GPT2-XL (1.5B)\n\n- Covid-19 specific version of 'malteos/gpt2-xl-wechsel-german'\n- Fine-tuned on 2 GB text from OSCAR filtered for covid related terms.",
"### How to use\n\nYou can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we\... | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #de #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
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image-classification | fastai | ## Model description
This repo contains the trained model for grapevine leaves image classification
Full credits go to [Vu Minh Chien](https://www.linkedin.com/in/vumichien/)
Motivation: The main product of grapevines is grapes that are consumed fresh or processed. In addition, grapevine leaves are harvested once a y... | {"tags": ["fastai", "image-classification"]} | hugginglearners/grapevine_leaves_classification | null | [
"fastai",
"image-classification",
"has_space",
"region:us"
] | null | 2022-07-08T12:16:44+00:00 | [] | [] | TAGS
#fastai #image-classification #has_space #region-us
| Model description
-----------------
This repo contains the trained model for grapevine leaves image classification
Full credits go to Vu Minh Chien
Motivation: The main product of grapevines is grapes that are consumed fresh or processed. In addition, grapevine leaves are harvested once a year as a by-product. Th... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:"
] | [
"TAGS\n#fastai #image-classification #has_space #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:"
] |
text-generation | transformers |
# Japanese GPT2 Lyric Model
## Model description
The model is used to generate Japanese lyrics.
## How to use
```python
import torch
from transformers import T5Tokenizer, GPT2LMHeadModel
device = torch.device("cpu")
if torch.cuda.is_available():
device = torch.device("cuda")
tokenizer = T5Tokenizer.from_pret... | {"language": "ja", "license": "mit", "tags": ["ja", "japanese", "gpt2", "text-generation", "lm", "nlp"], "datasets": ["skytnt/japanese-lyric"], "widget": [{"text": "<s>\u685c[CLS]"}]} | skytnt/gpt2-japanese-lyric-medium | null | [
"transformers",
"pytorch",
"tf",
"safetensors",
"gpt2",
"text-generation",
"ja",
"japanese",
"lm",
"nlp",
"dataset:skytnt/japanese-lyric",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-07-08T12:28:12+00:00 | [] | [
"ja"
] | TAGS
#transformers #pytorch #tf #safetensors #gpt2 #text-generation #ja #japanese #lm #nlp #dataset-skytnt/japanese-lyric #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# Japanese GPT2 Lyric Model
## Model description
The model is used to generate Japanese lyrics.
## How to use
## Training data
Training data contains 143,587 Japanese lyrics which are collected from uta-net by lyric_download | [
"# Japanese GPT2 Lyric Model",
"## Model description\n\nThe model is used to generate Japanese lyrics.",
"## How to use",
"## Training data\n\nTraining data contains 143,587 Japanese lyrics which are collected from uta-net by lyric_download"
] | [
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"# Japanese GPT2 Lyric Model",
"## Model description\n\nThe model is used to ... |
null | keras |
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
| name | learning_rate | decay | beta_1 | beta... | {"library_name": "keras"} | akraut/dummy_bin_image_clf | null | [
"keras",
"region:us"
] | null | 2022-07-08T12:39:46+00:00 | [] | [] | TAGS
#keras #region-us
| Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
Training and evaluation data
----------------------------
More information needed
Training procedure
------------------
### Training hyperparameters
The following h... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n\nModel Plot\n----------\n\n\n\nView Model Plot\n!Model Image"
] | [
"TAGS\n#keras #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n\nModel Plot\n----------\n\n\n\nView Model Plot\n!Model Image"
] |
null | null |
[gitattributes](/.gitattributes)
[gitattributes](./.gitattributes)
hi world | {"license": "mit"} | coyotte508/test-zzz_eee | null | [
"license:mit",
"region:us"
] | null | 2022-07-08T12:40:39+00:00 | [] | [] | TAGS
#license-mit #region-us
|
gitattributes
gitattributes
hi world | [] | [
"TAGS\n#license-mit #region-us \n"
] |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SPECTER-with-biblio-context-finetuned-review_classifier
This model is a fine-tuned version of [allenai/specter](https://huggingf... | {"license": "apache-2.0", "tags": ["text-classification", "generated_from_trainer"], "metrics": ["accuracy", "f1", "recall", "precision"], "model-index": [{"name": "SPECTER-with-biblio-context-finetuned-review_classifier", "results": []}]} | domenicrosati/SPECTER-with-biblio-context-finetuned-review_classifier | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T12:43:12+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| SPECTER-with-biblio-context-finetuned-review\_classifier
========================================================
This model is a fine-tuned version of allenai/specter on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1284
* Accuracy: 0.962
* F1: 0.7892
* Recall: 0.7593
* Pre... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 4.5e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\_size: 12\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\\_ste... | [
"TAGS\n#transformers #pytorch #bert #text-classification #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: 4.5e-05\n* train\\_batch\\_size: 12\n* eval\\_batch\\_size:... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-es_s51
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that you... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-es_s51 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:10:08+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-es_s51
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).
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_th_vp-es_s51\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-es_s51\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice... |
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-ft650_10class
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingf... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-ft650_10class", "results": []}]} | dminiotas05/distilbert-base-uncased-finetuned-ft650_10class | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:33:27+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-ft650\_10class
================================================
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.9674
* Accuracy: 0.2207
* F1: 0.2002
Model description
---------... | [
"### 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 #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_b... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-es_s552
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-es_s552 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:35:02+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-es_s552
Fine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).
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_th_vp-es_s552\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-es_s552\n\nFine-tuned facebook/wav2vec2-large-es-voxpopuli for speech recognition using the train split of Common Voic... |
reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit5
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-helicopter", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopter-PLE... | Guillaume63/Reinforce-helicopter | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2022-07-08T13:41:33+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL
| [
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 5 of the Deep Reinforcement Learning Class: URL"
] | [
"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 5 of ... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-nl_s569
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-nl_s569 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:44:43+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-nl_s569
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).
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_th_vp-nl_s569\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-nl_s569\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-nl_s253
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-nl_s253 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:49:10+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-nl_s253
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).
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_th_vp-nl_s253\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-nl_s253\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voic... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_vp-nl_s947
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that yo... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_vp-nl_s947 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:52:36+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_vp-nl_s947
Fine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).
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_th_vp-nl_s947\n\nFine-tuned facebook/wav2vec2-large-nl-voxpopuli for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_vp-nl_s947\n\nFine-tuned facebook/wav2vec2-large-nl-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-distilled-clinc
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["clinc_oos"], "metrics": ["accuracy"], "model-index": [{"name": "distilbert-base-uncased-distilled-clinc", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "clinc_oos", "type": "clinc_oos",... | tfshaman/distilbert-base-uncased-distilled-clinc | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:clinc_oos",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:52:51+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-clinc_oos #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-distilled-clinc
=======================================
This model is a fine-tuned version of distilbert-base-uncased on the clinc\_oos dataset.
It achieves the following results on the evaluation set:
* Loss: 1.5565
* Accuracy: 0.8265
Model description
-----------------
More information... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 48\n* eval\\_batch\\_size: 48\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-clinc_oos #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate:... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech-sat_s658
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech-sat_s658 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T13:56:29+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech-sat_s658
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (th).
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_th_unispeech-sat_s658\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech-sat_s658\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech-sat_s515
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech-sat_s515 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:00:21+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech-sat_s515
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (th).
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_th_unispeech-sat_s515\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech-sat_s515\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
video-classification | transformers |
# VideoMAE (base-sized model, fine-tuned on Kinetics-400)
VideoMAE model pre-trained for 1600 epochs in a self-supervised way and fine-tuned in a supervised way on Kinetics-400. It was introduced in the paper [VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training](https://a... | {"license": "cc-by-nc-4.0", "tags": ["vision", "video-classification"]} | MCG-NJU/videomae-base-finetuned-kinetics | null | [
"transformers",
"pytorch",
"videomae",
"video-classification",
"vision",
"arxiv:2203.12602",
"arxiv:2111.06377",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-07-08T14:01:34+00:00 | [
"2203.12602",
"2111.06377"
] | [] | TAGS
#transformers #pytorch #videomae #video-classification #vision #arxiv-2203.12602 #arxiv-2111.06377 #license-cc-by-nc-4.0 #endpoints_compatible #has_space #region-us
|
# VideoMAE (base-sized model, fine-tuned on Kinetics-400)
VideoMAE model pre-trained for 1600 epochs in a self-supervised way and fine-tuned in a supervised way on Kinetics-400. It was introduced in the paper VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training by Tong et ... | [
"# VideoMAE (base-sized model, fine-tuned on Kinetics-400) \n\nVideoMAE model pre-trained for 1600 epochs in a self-supervised way and fine-tuned in a supervised way on Kinetics-400. It was introduced in the paper VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training by To... | [
"TAGS\n#transformers #pytorch #videomae #video-classification #vision #arxiv-2203.12602 #arxiv-2111.06377 #license-cc-by-nc-4.0 #endpoints_compatible #has_space #region-us \n",
"# VideoMAE (base-sized model, fine-tuned on Kinetics-400) \n\nVideoMAE model pre-trained for 1600 epochs in a self-supervised way and fi... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_unispeech-sat_s772
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spe... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_unispeech-sat_s772 | null | [
"transformers",
"pytorch",
"unispeech-sat",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:03:49+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #unispeech-sat #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_unispeech-sat_s772
Fine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (th).
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_th_unispeech-sat_s772\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_unispeech-sat_s772\n\nFine-tuned microsoft/unispeech-sat-large for speech recognition using the train split of Commo... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_xls-r_s625
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_xls-r_s625 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:07:26+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_xls-r_s625
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (th).
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_th_xls-r_s625\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_xls-r_s625\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (t... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```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... | sigalaz/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2022-07-08T14:08:39+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_th_xls-r_s879
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_xls-r_s879 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:11:20+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_xls-r_s879
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (th).
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_th_xls-r_s879\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_xls-r_s879\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (t... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_xls-r_s590
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your speech input ... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_xls-r_s590 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:14:26+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_xls-r_s590
Fine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (th).
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_th_xls-r_s590\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_xls-r_s590\n\nFine-tuned facebook/wav2vec2-xls-r-300m for speech recognition using the train split of Common Voice 7.0 (t... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_r-wav2vec2_s805
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_r-wav2vec2_s805 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:17:48+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_r-wav2vec2_s805
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (th).
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_th_r-wav2vec2_s805\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_r-wav2vec2_s805\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
text2text-generation | transformers | ## Model overview
This model was trained in terms of [GenChal 2022: Feedback Comment Generation for Writing Learning](https://fcg.sharedtask.org/) shared task
In this task, the model gets the string with text with the error and the exact span of the error and should return the comment in natural language, which expla... | {"language": ["en"], "tags": ["feedback comment generation for writing learning"], "licenses": ["cc-by-nc-sa"]} | s-nlp/GenChal_2022_nigula | null | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"feedback comment generation for writing learning",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-07-08T14:17:59+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #t5 #text2text-generation #feedback comment generation for writing learning #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| ## Model overview
This model was trained in terms of GenChal 2022: Feedback Comment Generation for Writing Learning shared task
In this task, the model gets the string with text with the error and the exact span of the error and should return the comment in natural language, which explains the nature of the error.
... | [
"## Model overview\n\nThis model was trained in terms of GenChal 2022: Feedback Comment Generation for Writing Learning shared task\n\nIn this task, the model gets the string with text with the error and the exact span of the error and should return the comment in natural language, which explains the nature of the ... | [
"TAGS\n#transformers #pytorch #t5 #text2text-generation #feedback comment generation for writing learning #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## Model overview\n\nThis model was trained in terms of GenChal 2022: Feedback Comment Generation for Writing Learni... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# bert-dummy-seq
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "bert-dummy-seq", "results": []}]} | Rocketknight1/bert-dummy-seq | null | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:18:33+00:00 | [] | [] | TAGS
#transformers #tf #bert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# bert-dummy-seq
This model is a fine-tuned version of bert-base-cased on an unknown dataset.
It achieves the following results on the evaluation set:
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
#... | [
"# bert-dummy-seq\n\nThis model is a fine-tuned version of bert-base-cased on an unknown dataset.\nIt achieves the following results on the evaluation set:",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore... | [
"TAGS\n#transformers #tf #bert #text-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# bert-dummy-seq\n\nThis model is a fine-tuned version of bert-base-cased on an unknown dataset.\nIt achieves the following results on the evaluation ... |
automatic-speech-recognition | transformers | # exp_w2v2t_th_r-wav2vec2_s930
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 (th)](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0).
When using this model, make sure that your spee... | {"language": ["th"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "th"], "datasets": ["mozilla-foundation/common_voice_7_0"]} | jonatasgrosman/exp_w2v2t_th_r-wav2vec2_s930 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"th",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-07-08T14:21:42+00:00 | [] | [
"th"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us
| # exp_w2v2t_th_r-wav2vec2_s930
Fine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (th).
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_th_r-wav2vec2_s930\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice 7.0 (th).\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 #th #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #endpoints_compatible #region-us \n",
"# exp_w2v2t_th_r-wav2vec2_s930\n\nFine-tuned facebook/wav2vec2-large-robust for speech recognition using the train split of Common Voice... |
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