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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/dis... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "con... | indridinn/distilbert-base-uncased-finetuned-ner | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-ner
=====================================
This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0610
* Precision: 0.9275
* Recall: 0.9370
* F1: 0.9322
* Accuracy: 0.9836
Model des... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* le... |
automatic-speech-recognition | transformers |
Dummy Model New | {"language": "id", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "XLSR Wav2Vec2 Indonesian by cahya", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech ... | inergi/wav2vec2-from-scratch-finetune-dummy | null | [
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"audio",
"speech",
"xlsr-fine-tuning-week",
"id",
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"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"id"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #id #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
Dummy Model New | [] | [
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] |
automatic-speech-recognition | transformers | # Wav2Vec2-Large-XLSR-53-Assamese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Assamese using the [Common Voice](https://huggingface.co/datasets/common_voice).
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can b... | {"language": "as", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "Joydeep Bhattacharjee XLSR Wav2Vec2 Large 53 Assamese", "results": [{"task": {"type": "automatic-speech-recognitio... | infinitejoy/Wav2Vec2-Large-XLSR-53-Assamese | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"as",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"as"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #as #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
| # Wav2Vec2-Large-XLSR-53-Assamese
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Assamese using the Common Voice.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follow... | [
"# Wav2Vec2-Large-XLSR-53-Assamese\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Assamese using the Common Voice.\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\nThe model can be e... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #as #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Assamese\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Assamese using the Com... |
automatic-speech-recognition | transformers | # Wav2Vec2-Large-XLSR-53-Odia
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Odia using the [Common Voice](https://huggingface.co/datasets/common_voice).
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used d... | {"language": "or", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "Joydeep Bhattacharjee XLSR Wav2Vec2 Large 53 Odia", "results": [{"task": {"type": "automatic-speech-recognition", ... | infinitejoy/Wav2Vec2-Large-XLSR-53-Odia | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"or",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"or"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #or #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
| # Wav2Vec2-Large-XLSR-53-Odia
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Odia using the Common Voice.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the... | [
"# Wav2Vec2-Large-XLSR-53-Odia\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Odia using the Common Voice.\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\nThe model can be evaluated... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #or #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Odia\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Odia using the Common Voic... |
automatic-speech-recognition | transformers | # Wav2Vec2-Large-XLSR-53-Tamil
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Tamil using the [Common Voice](https://huggingface.co/datasets/common_voice).
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used... | {"language": "ta", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "Joydeep Bhattacharjee XLSR Wav2Vec2 Large 53 Tamil", "results": [{"task": {"type": "automatic-speech-recognition",... | infinitejoy/Wav2Vec2-Large-XLSR-53-Tamil | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"ta",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ta"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #ta #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
| # Wav2Vec2-Large-XLSR-53-Tamil
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Tamil using the Common Voice.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on t... | [
"# Wav2Vec2-Large-XLSR-53-Tamil\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Tamil using the Common Voice.\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\nThe model can be evaluat... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #ta #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Tamil\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Tamil using the Common Vo... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-abkhaz-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co... | {"language": ["ab"], "license": "apache-2.0", "tags": ["ab", "automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-300M - Abkhaz... | infinitejoy/wav2vec2-large-xls-r-300m-abkhaz-cv8 | null | [
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"wav2vec2",
"automatic-speech-recognition",
"ab",
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"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ab"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ab #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-abkhaz-cv8
====================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - AB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1614
* Wer: 0.2907
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ab #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-abkhaz
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["ab"], "license": "apache-2.0", "tags": ["ab", "automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Abkhaz", "results": [{"t... | infinitejoy/wav2vec2-large-xls-r-300m-abkhaz | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ab",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ab"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ab #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-abkhaz
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - AB dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5359
* Wer: 0.6192
Model description
-----------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ab #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperpar... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# XLS-R-300m-SV
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-... | {"language": ["ar"], "license": "apache-2.0", "tags": ["ar", "automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Arabic... | infinitejoy/wav2vec2-large-xls-r-300m-arabic | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ar"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ar #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| XLS-R-300m-SV
=============
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - AR dataset.
It achieves the following results on the evaluation set:
* Loss: NA
* Wer: NA
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7.5e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #ar #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-armenian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"language": ["hy-AM"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Armenian", "results": [{"ta... | infinitejoy/wav2vec2-large-xls-r-300m-armenian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"re... | null | 2022-03-02T23:29:05+00:00 | [] | [
"hy-AM"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-armenian
==================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - HY-AM dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9669
* Wer: 0.6942
Model description
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperparamet... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-assamese-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.... | {"language": ["as"], "license": "apache-2.0", "tags": ["as", "automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-300M - Assame... | infinitejoy/wav2vec2-large-xls-r-300m-assamese-cv8 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"as",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"as"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #as #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-assamese-cv8
======================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - AS dataset.
It achieves the following results on the evaluation set:
* Loss: 0.9814
* Wer: 0.7402
Model description
-----... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #as #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
# wav2vec2-large-xls-r-300m-assamese
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_7_0 dataset.
It achieves the following results on the evaluation set:
- WER: 0.7954545454545454
- CER: 0.32341269841269843
## Model descr... | {"language": "as", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning", "as", "robust-speech-event", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Assamese", "results": [{"task": {"type": "automatic-... | infinitejoy/wav2vec2-large-xls-r-300m-assamese | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning",
"as",
"robust-speech-event",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"r... | null | 2022-03-02T23:29:05+00:00 | [] | [
"as"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning #as #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-assamese
==================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice\_7\_0 dataset.
It achieves the following results on the evaluation set:
* WER: 0.7954545454545454
* CER: 0.32341269841269843
Model description
-------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-4\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: not given\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and ep... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning #as #robust-speech-event #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nTh... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-basaa-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["bas"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "bas", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-300M - Basa... | infinitejoy/wav2vec2-large-xls-r-300m-basaa-cv8 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"bas",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
... | null | 2022-03-02T23:29:05+00:00 | [] | [
"bas"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #bas #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-basaa-cv8
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - BAS dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4648
* Wer: 0.5472
Model description
----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #bas #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### ... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-basaa
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["bas"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Basaa", "results": [{"task": ... | infinitejoy/wav2vec2-large-xls-r-300m-basaa | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"bas",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatibl... | null | 2022-03-02T23:29:05+00:00 | [] | [
"bas"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #bas #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-basaa
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - BAS dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5975
* Wer: 0.4981
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #bas #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperpa... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-bashkir
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["ba"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Bashkir", "results": [{"task":... | infinitejoy/wav2vec2-large-xls-r-300m-bashkir | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"ba",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ba"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #ba #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-bashkir
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - BA dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1892
* Wer: 0.2421
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #ba #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperpar... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# XLS-R-300M - Breton
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec... | {"language": ["br"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "br", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-300M - Breton... | infinitejoy/wav2vec2-large-xls-r-300m-breton-cv8 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"br",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"br"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #br #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# XLS-R-300M - Breton
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BR dataset.
It achieves the following results on the evaluation set:
- Loss: NA
- Wer: NA
## Model description
More information needed
## Intended uses & limitations
More informa... | [
"# XLS-R-300M - Breton\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BR dataset.\nIt achieves the following results on the evaluation set:\n- Loss: NA\n- Wer: NA",
"## Model description\n\nMore information needed",
"## Intended uses & limitati... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #br #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# XLS... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-breton
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["br"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Breton", "results": [{"task": ... | infinitejoy/wav2vec2-large-xls-r-300m-breton | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"br",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible... | null | 2022-03-02T23:29:05+00:00 | [] | [
"br"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #br #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-breton
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - BR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6102
* Wer: 0.4455
Model description
-----------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #robust-speech-event #br #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperpar... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-bulgarian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["bg"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "bg", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Bulgar... | infinitejoy/wav2vec2-large-xls-r-300m-bulgarian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"bg",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"bg"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #bg #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-bulgarian
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - BG dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4487
* Wer: 0.4674
Model description
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #bg #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-chuvash
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["cv"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "cv", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Chuvas... | infinitejoy/wav2vec2-large-xls-r-300m-chuvash | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"cv",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"cv"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #cv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-chuvash
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - CV dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7651
* Wer: 0.6166
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #cv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-finnish
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["fi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fi", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Finnis... | infinitejoy/wav2vec2-large-xls-r-300m-finnish | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fi",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"fi"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fi #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-finnish
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - FI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2307
* Wer: 0.2984
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fi #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-galician
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"language": ["gl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "gl", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Galici... | infinitejoy/wav2vec2-large-xls-r-300m-galician | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"gl",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"gl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #gl #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-galician
==================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - GL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1525
* Wer: 0.1542
Model description
-------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #gl #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-georgian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"language": ["ka"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "ka", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Georgi... | infinitejoy/wav2vec2-large-xls-r-300m-georgian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"ka",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ka"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ka #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-georgian
==================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - KA dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3666
* Wer: 0.4211
Model description
-------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ka #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-greek
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["el"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "el", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Greek"... | infinitejoy/wav2vec2-large-xls-r-300m-greek | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"el",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"el"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #el #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-greek
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - EL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6592
* Wer: 0.4564
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #el #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-hausa
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["ha"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "ha", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Hausa"... | infinitejoy/wav2vec2-large-xls-r-300m-hausa | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"ha",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ha"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ha #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hausa
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - HA dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5756
* Wer: 0.6014
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ha #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-hindi
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["hi"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "hi", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Hindi"... | infinitejoy/wav2vec2-large-xls-r-300m-hindi | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"hi",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"hi"
] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #hi #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hindi
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - HI dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5414
* Wer: 1.0194
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7.5e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_ste... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #hi #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us ... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-hungarian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["hu"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "hu", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Hungar... | infinitejoy/wav2vec2-large-xls-r-300m-hungarian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"hu",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"hu"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #hu #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-hungarian
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - HU dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2562
* Wer: 0.3112
Model description
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #hu #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-indonesian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co... | {"language": ["id"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-indonesian", "results": []}]} | infinitejoy/wav2vec2-large-xls-r-300m-indonesian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"id",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"id"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #id #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-indonesian
====================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - ID dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2759
* Wer: 0.3256
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #id #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* ... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-irish
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["ga-IE"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "ga-IE", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - ... | infinitejoy/wav2vec2-large-xls-r-300m-irish | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"ga-IE",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ga-IE"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ga-IE #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-irish
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - GA-IE dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1647
* Wer: 0.7296
Model description
----------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 4\n* total\\_train\\_batch\\_size: 256\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ga-IE #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"##... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-kurdish
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["kmr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "kmr", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Kurm... | infinitejoy/wav2vec2-large-xls-r-300m-kurdish | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"kmr",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
... | null | 2022-03-02T23:29:05+00:00 | [] | [
"kmr"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #kmr #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| wav2vec2-large-xls-r-300m-kurdish
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - KMR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2548
* Wer: 0.2688
Model description
--------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #kmr #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-kyrgyz
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["ky"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "ky", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Kyrgyz... | infinitejoy/wav2vec2-large-xls-r-300m-kyrgyz | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"ky",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ky"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ky #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-kyrgyz
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - KY dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5817
* Wer: 0.4096
Model description
-----------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ky #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-latvian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["lv"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "lv", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Latvia... | infinitejoy/wav2vec2-large-xls-r-300m-latvian | null | [
"transformers",
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"lv",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"lv"
] | TAGS
#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #lv #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-latvian
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - LV dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1892
* Wer: 0.1698
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #safetensors #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #lv #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us ... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-lithuanian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co... | {"language": ["lt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "lt", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Lithua... | infinitejoy/wav2vec2-large-xls-r-300m-lithuanian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"lt",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"lt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #lt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-lithuanian
====================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - LT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1722
* Wer: 0.2486
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #lt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-maltese
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fa... | {"language": ["mt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "mt", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Maltes... | infinitejoy/wav2vec2-large-xls-r-300m-maltese | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"mt",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"mt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #mt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-maltese
=================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - MT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2005
* Wer: 0.1897
Model description
---------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #mt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-marathi-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.c... | {"language": ["mr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer", "mr", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-300M - Marath... | infinitejoy/wav2vec2-large-xls-r-300m-marathi-cv8 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"mr",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"mr"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mr #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-marathi-cv8
=====================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - MR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6483
* Wer: 0.6049
Model description
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #mr #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-mongolian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["mn"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mn", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Mongol... | infinitejoy/wav2vec2-large-xls-r-300m-mongolian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mn",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"mn"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mn #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-mongolian
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - MN dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6003
* Wer: 0.4473
Model description
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mn #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-odia-cv8
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"language": ["or"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_8_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-odia-cv8", "results": []}]} | infinitejoy/wav2vec2-large-xls-r-300m-odia-cv8 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"or",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"or"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #or #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-odia-cv8
==================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - OR dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8176
* Wer: 0.5818
Model description
-------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_step... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_8_0 #generated_from_trainer #or #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* ... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-odia
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/faceb... | {"language": ["or"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "or", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Odia", "results": [{"tas... | infinitejoy/wav2vec2-large-xls-r-300m-odia | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"or",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible... | null | 2022-03-02T23:29:05+00:00 | [] | [
"or"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #or #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| wav2vec2-large-xls-r-300m-odia
==============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - OR dataset.
It achieves the following results on the evaluation set:
* WER: 1.0921052631578947
* CER: 2.5547945205479454
Model descriptio... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7.5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsil... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_7_0 #or #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"### Traini... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-romanian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/f... | {"language": ["ro"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "ro", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Romani... | infinitejoy/wav2vec2-large-xls-r-300m-romanian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"ro",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ro"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #ro #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-romanian
==================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - RO dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1167
* Wer: 0.1421
Model description
-------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #ro #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-romansh-sursilvan
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://hugging... | {"language": ["rm-sursilv"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "rm-sursilv", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS... | infinitejoy/wav2vec2-large-xls-r-300m-romansh-sursilvan | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"rm-sursilv",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-ind... | null | 2022-03-02T23:29:05+00:00 | [] | [
"rm-sursilv"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #rm-sursilv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-romansh-sursilvan
===========================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - RM-SURSILV dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2163
* Wer: 0.1981
Model... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #rm-sursilv #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-romansh-vallader
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingf... | {"language": ["rm-vallader"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "rm-vallader", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "X... | infinitejoy/wav2vec2-large-xls-r-300m-romansh-vallader | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"rm-vallader",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-in... | null | 2022-03-02T23:29:05+00:00 | [] | [
"rm-vallader"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #rm-vallader #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-romansh-vallader
==========================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - RM-VALLADER dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3155
* Wer: 0.3162
Model ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #rm-vallader #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-sakha
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["sah"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "sah", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Sakh... | infinitejoy/wav2vec2-large-xls-r-300m-sakha | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"sah",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
... | null | 2022-03-02T23:29:05+00:00 | [] | [
"sah"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sah #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-sakha
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - SAH dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4995
* Wer: 0.4421
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sah #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### ... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-slovak
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/fac... | {"language": ["sk"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "sk", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Slovak... | infinitejoy/wav2vec2-large-xls-r-300m-slovak | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"sk",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"sk"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-slovak
================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - SK dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2915
* Wer: 0.2481
Model description
-----------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps:... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sk #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-slovenian
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/... | {"language": ["sl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "sl", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Sloven... | infinitejoy/wav2vec2-large-xls-r-300m-slovenian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"sl",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"sl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-slovenian
===================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - SL dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2093
* Wer: 0.1907
Model description
-----------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #sl #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-tatar
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["tt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer", "tt", "robust-speech-event", "model_for_talk", "hf-asr-leaderboard"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Tatar"... | infinitejoy/wav2vec2-large-xls-r-300m-tatar | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"tt",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"tt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #tt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-tatar
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - TT dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1959
* Wer: 0.2454
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #tt #robust-speech-event #model_for_talk #hf-asr-leaderboard #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
infinitejoy/wav2vec2-large-xls-r-300m-urdu
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingfac... | {"language": ["ur"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event", "ur"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Urdu",... | infinitejoy/wav2vec2-large-xls-r-300m-urdu | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"ur",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ur"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #ur #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
infinitejoy/wav2vec2-large-xls-r-300m-urdu
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - -UR dataset.
It achieves the following results on the evaluation set:
- Loss: NA
- Wer: NA
## Model description
More information needed
## Intended uses & lim... | [
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training hyperparameters\n\nThe following hyperparameters were used during training:\n- learning_rate: 7... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #ur #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"## Mo... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-welsh
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/face... | {"language": ["cy"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "cy", "generated_from_trainer", "hf-asr-leaderboard", "model_for_talk", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "XLS-R-300M - Welsh"... | infinitejoy/wav2vec2-large-xls-r-300m-welsh | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"cy",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_7_0",
"license:apache-2.0",
"model-index",
"... | null | 2022-03-02T23:29:05+00:00 | [] | [
"cy"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #cy #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-welsh
===============================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_7\_0 - CY dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2650
* Wer: 0.2702
Model description
-----------------
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 7e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #cy #generated_from_trainer #hf-asr-leaderboard #model_for_talk #mozilla-foundation/common_voice_7_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_7_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### T... |
text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-fi-to-en
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wmt19 datas... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wmt19"], "metrics": ["bleu"], "model-index": [{"name": "t5-small-finetuned-fi-to-en", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wmt19", "type": "wmt19", "args":... | ingridnc/t5-small-finetuned-fi-to-en | null | [
"transformers",
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:wmt19",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wmt19 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| t5-small-finetuned-fi-to-en
===========================
This model is a fine-tuned version of t5-small on the wmt19 dataset.
It achieves the following results on the evaluation set:
* Loss: 3.3598
* Bleu: 1.618
* Gen Len: 17.3223
Model description
-----------------
More information needed
Intended uses & limi... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5\n* mixed\\_prec... | [
"TAGS\n#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-wmt19 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during trai... |
sentence-similarity | sentence-transformers |
# inokufu/bertheo
A [sentence-transformers](https://www.SBERT.net) model fine-tuned on course sentences. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Details
This model is based on the French flaubert-base-uncased pre-trained... | {"language": "fr", "tags": ["sentence-similarity", "transformers", "Education", "fr", "flaubert", "sentence-transformers", "feature-extraction", "xnli", "stsb_multi_mt"], "datasets": ["xnli", "stsb_multi_mt"], "pipeline_tag": "sentence-similarity"} | inokufu/flaubert-base-uncased-xnli-sts-finetuned-education | null | [
"sentence-transformers",
"pytorch",
"flaubert",
"feature-extraction",
"sentence-similarity",
"transformers",
"Education",
"fr",
"xnli",
"stsb_multi_mt",
"dataset:xnli",
"dataset:stsb_multi_mt",
"arxiv:1810.04805",
"arxiv:1809.05053",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1810.04805",
"1809.05053"
] | [
"fr"
] | TAGS
#sentence-transformers #pytorch #flaubert #feature-extraction #sentence-similarity #transformers #Education #fr #xnli #stsb_multi_mt #dataset-xnli #dataset-stsb_multi_mt #arxiv-1810.04805 #arxiv-1809.05053 #endpoints_compatible #region-us
|
# inokufu/bertheo
A sentence-transformers model fine-tuned on course sentences. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Details
This model is based on the French flaubert-base-uncased pre-trained model [1, 2].
It was f... | [
"# inokufu/bertheo\n\nA sentence-transformers model fine-tuned on course sentences. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.",
"## Details\n\nThis model is based on the French flaubert-base-uncased pre-trained model [1, 2]... | [
"TAGS\n#sentence-transformers #pytorch #flaubert #feature-extraction #sentence-similarity #transformers #Education #fr #xnli #stsb_multi_mt #dataset-xnli #dataset-stsb_multi_mt #arxiv-1810.04805 #arxiv-1809.05053 #endpoints_compatible #region-us \n",
"# inokufu/bertheo\n\nA sentence-transformers model fine-tuned ... |
sentence-similarity | sentence-transformers |
# inokufu/flaubert-base-uncased-xnli-sts
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Details
This model is based on the French flaubert-base-uncased pre-trained... | {"language": "fr", "tags": ["sentence-similarity", "transformers", "fr", "flaubert", "sentence-transformers", "feature-extraction", "xnli", "stsb_multi_mt"], "datasets": ["xnli", "stsb_multi_mt"], "pipeline_tag": "sentence-similarity"} | inokufu/flaubert-base-uncased-xnli-sts | null | [
"sentence-transformers",
"pytorch",
"flaubert",
"feature-extraction",
"sentence-similarity",
"transformers",
"fr",
"xnli",
"stsb_multi_mt",
"dataset:xnli",
"dataset:stsb_multi_mt",
"arxiv:1809.05053",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1809.05053"
] | [
"fr"
] | TAGS
#sentence-transformers #pytorch #flaubert #feature-extraction #sentence-similarity #transformers #fr #xnli #stsb_multi_mt #dataset-xnli #dataset-stsb_multi_mt #arxiv-1809.05053 #endpoints_compatible #region-us
|
# inokufu/flaubert-base-uncased-xnli-sts
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Details
This model is based on the French flaubert-base-uncased pre-trained model [1, 2].
It was th... | [
"# inokufu/flaubert-base-uncased-xnli-sts\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.",
"## Details\n\nThis model is based on the French flaubert-base-uncased pre-trained model [1, 2]... | [
"TAGS\n#sentence-transformers #pytorch #flaubert #feature-extraction #sentence-similarity #transformers #fr #xnli #stsb_multi_mt #dataset-xnli #dataset-stsb_multi_mt #arxiv-1809.05053 #endpoints_compatible #region-us \n",
"# inokufu/flaubert-base-uncased-xnli-sts\n\nThis is a sentence-transformers model: It maps ... |
text-classification | transformers |
# Multi2ConvAI-Corona: finetuned Bert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: German (de)
- model type:... | {"language": "de", "license": "mit", "tags": ["text-classification", "pytorch", "transformers"], "widget": [{"text": "Muss ich eine Maske tragen?"}]} | inovex/multi2convai-corona-de-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Corona: finetuned Bert for German
This model was developed in the Multi2ConvAI project:
- domain: Corona (more details about our use cases: (en, de))
- language: German (de)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface Trans... | [
"# Multi2ConvAI-Corona: finetuned Bert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### Run ... | [
"TAGS\n#transformers #pytorch #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Corona: finetuned Bert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n... |
text-classification | null |
# Multi2ConvAI-Corona: German logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- lang... | {"language": "de", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-corona-de-logreg-ft | null | [
"text-classification",
"de",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#text-classification #de #license-mit #region-us
|
# Multi2ConvAI-Corona: German logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Corona (more details about our use cases: (en, de))
- language: German (de)
- model type: logistic regression
- embeddings: fastText embeddings
## How to run
R... | [
"# Multi2ConvAI-Corona: German logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings",
"#... | [
"TAGS\n#text-classification #de #license-mit #region-us \n",
"# Multi2ConvAI-Corona: German logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: ... |
text-classification | transformers |
# Multi2ConvAI-Corona: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: English (en)
- model typ... | {"language": "en", "license": "mit", "tags": ["text-classification", "pytorch", "transformers"], "widget": [{"text": "Do I need to wear a mask?"}]} | inovex/multi2convai-corona-en-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Corona: finetuned Bert for English
This model was developed in the Multi2ConvAI project:
- domain: Corona (more details about our use cases: (en, de))
- language: English (en)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface Tra... | [
"# Multi2ConvAI-Corona: finetuned Bert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### Ru... | [
"TAGS\n#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Corona: finetuned Bert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\... |
text-classification | null |
# Multi2ConvAI-Corona: English logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- lan... | {"language": "en", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-corona-en-logreg-ft | null | [
"text-classification",
"en",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#text-classification #en #license-mit #region-us
|
# Multi2ConvAI-Corona: English logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Corona (more details about our use cases: (en, de))
- language: English (en)
- model type: logistic regression
- embeddings: fastText embeddings
## How to run
... | [
"# Multi2ConvAI-Corona: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings",
... | [
"TAGS\n#text-classification #en #license-mit #region-us \n",
"# Multi2ConvAI-Corona: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type... |
text-classification | transformers |
# Multi2ConvAI-Corona: finetuned Bert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2conv.ai/en/blog/use-cases), [de](https://multi2conv.ai/en/blog/use-cases)))
- language: French (fr)
- model type: fin... | {"language": "fr", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Dois-je porter un masque?"}]} | inovex/multi2convai-corona-fr-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"fr",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #bert #text-classification #fr #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Corona: finetuned Bert for French
This model was developed in the Multi2ConvAI project:
- domain: Corona (more details about our use cases: (en, de))
- language: French (fr)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface Transformers
'
#... | [
"# Multi2ConvAI-Corona: finetuned Bert for French \n\nThis model was developed in the Multi2ConvAI project:\n- domain: Corona (more details about our use cases: (en, de))\n- language: French (fr)\n- model type: finetuned Bert",
"## How to run\n\nRequires: \n- Huggingface transformers",
"### Run with Huggingface... | [
"TAGS\n#transformers #pytorch #bert #text-classification #fr #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Corona: finetuned Bert for French \n\nThis model was developed in the Multi2ConvAI project:\n- domain: Corona (more details about our use cases: (en, de))\n- langua... |
text-classification | transformers |
# Multi2ConvAI-Corona: finetuned Bert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: Italian (it)
- model typ... | {"language": "it", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Devo indossare una maschera?"}]} | inovex/multi2convai-corona-it-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"it",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #bert #text-classification #it #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Corona: finetuned Bert for Italian
This model was developed in the Multi2ConvAI project:
- domain: Corona (more details about our use cases: (en, de))
- language: Italian (it)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface Tra... | [
"# Multi2ConvAI-Corona: finetuned Bert for Italian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\n- language: Italian (it)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### Ru... | [
"TAGS\n#transformers #pytorch #bert #text-classification #it #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Corona: finetuned Bert for Italian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Corona (more details about our use cases: (en, de))\r\... |
text-classification | transformers |
# Multi2ConvAI-Logistics: finetuned Bert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: German (de)
- model... | {"language": "de", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Wo kann ich das Paket ablegen?"}]} | inovex/multi2convai-logistics-de-bert | null | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #safetensors #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Logistics: finetuned Bert for German
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: German (de)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface... | [
"# Multi2ConvAI-Logistics: finetuned Bert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"##... | [
"TAGS\n#transformers #pytorch #safetensors #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Logistics: finetuned Bert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use c... |
text-classification | null |
# Multi2ConvAI-Logistics: German logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
... | {"language": "de", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-logistics-de-logreg-ft | null | [
"text-classification",
"de",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#text-classification #de #license-mit #region-us
|
# Multi2ConvAI-Logistics: German logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: German (de)
- model type: logistic regression
- embeddings: fastText embeddings
## How to ru... | [
"# Multi2ConvAI-Logistics: German logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings"... | [
"TAGS\n#text-classification #de #license-mit #region-us \n",
"# Multi2ConvAI-Logistics: German logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model ... |
text-classification | transformers |
# Multi2ConvAI-Logistics: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: English (en)
- mod... | {"language": "en", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Where can I put the parcel?"}]} | inovex/multi2convai-logistics-en-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Logistics: finetuned Bert for English
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: English (en)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingfa... | [
"# Multi2ConvAI-Logistics: finetuned Bert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"... | [
"TAGS\n#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Logistics: finetuned Bert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, d... |
text-classification | null |
# Multi2ConvAI-Logistics: English logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
... | {"language": "en", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-logistics-en-logreg-ft | null | [
"text-classification",
"en",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#text-classification #en #license-mit #region-us
|
# Multi2ConvAI-Logistics: English logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: English (en)
- model type: logistic regression
- embeddings: fastText embeddings
## How to ... | [
"# Multi2ConvAI-Logistics: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: logistic regression\r\n- embeddings: fastText embedding... | [
"TAGS\n#text-classification #en #license-mit #region-us \n",
"# Multi2ConvAI-Logistics: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- mode... |
text-classification | transformers |
# Multi2ConvAI-Logistics: finetuned Bert for Croatian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: Croatian (hr)
- m... | {"language": "hr", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "gdje mogu staviti paket?"}]} | inovex/multi2convai-logistics-hr-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"hr",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hr"
] | TAGS
#transformers #pytorch #bert #text-classification #hr #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Logistics: finetuned Bert for Croatian
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: Croatian (hr)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Hugging... | [
"# Multi2ConvAI-Logistics: finetuned Bert for Croatian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: Croatian (hr)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
... | [
"TAGS\n#transformers #pytorch #bert #text-classification #hr #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Logistics: finetuned Bert for Croatian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, ... |
text-classification | transformers |
# Multi2ConvAI-Logistics: finetuned Bert for Polish
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: Polish (pl)
- model... | {"language": "pl", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "gdzie mog\u0119 umie\u015bci\u0107 paczk\u0119?"}]} | inovex/multi2convai-logistics-pl-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"pl",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pl"
] | TAGS
#transformers #pytorch #bert #text-classification #pl #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Logistics: finetuned Bert for Polish
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: Polish (pl)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface... | [
"# Multi2ConvAI-Logistics: finetuned Bert for Polish \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: Polish (pl)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"##... | [
"TAGS\n#transformers #pytorch #bert #text-classification #pl #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Logistics: finetuned Bert for Polish \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de... |
text-classification | transformers |
# Multi2ConvAI-Logistics: finetuned Bert for Turkish
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: Turkish (tr)
- mod... | {"language": "tr", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "paketi nereye koyabilirim?"}]} | inovex/multi2convai-logistics-tr-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"tr",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"tr"
] | TAGS
#transformers #pytorch #bert #text-classification #tr #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Logistics: finetuned Bert for Turkish
This model was developed in the Multi2ConvAI project:
- domain: Logistics (more details about our use cases: (en, de))
- language: Turkish (tr)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingfa... | [
"# Multi2ConvAI-Logistics: finetuned Bert for Turkish \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, de))\r\n- language: Turkish (tr)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"... | [
"TAGS\n#transformers #pytorch #bert #text-classification #tr #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Logistics: finetuned Bert for Turkish \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Logistics (more details about our use cases: (en, d... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned Bert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: German (de)
- model typ... | {"language": "de", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Starte das Programm"}]} | inovex/multi2convai-quality-de-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned Bert for German
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: German (de)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface Tra... | [
"# Multi2ConvAI-Quality: finetuned Bert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### Ru... | [
"TAGS\n#transformers #pytorch #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned Bert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r... |
text-classification | null |
# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- l... | {"language": "de", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-quality-de-logreg-ft | null | [
"text-classification",
"de",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#text-classification #de #license-mit #region-us
|
# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: German (de)
- model type: logistic regression
- embeddings: fastText embeddings
## How to run
... | [
"# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings",
... | [
"TAGS\n#text-classification #de #license-mit #region-us \n",
"# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model typ... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned MBert for German
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: German (de)
- model ty... | {"language": "de", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Starte das Programm"}]} | inovex/multi2convai-quality-de-mbert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"de",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned MBert for German
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: German (de)
- model type: finetuned MBert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface T... | [
"# Multi2ConvAI-Quality: finetuned MBert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: German (de)\r\n- model type: finetuned MBert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### ... | [
"TAGS\n#transformers #pytorch #bert #text-classification #de #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned MBert for German \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: English (en)
- model t... | {"language": "en", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Start the program"}]} | inovex/multi2convai-quality-en-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned Bert for English
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: English (en)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface T... | [
"# Multi2ConvAI-Quality: finetuned Bert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### ... | [
"TAGS\n#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned Bert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\... |
text-classification | null |
# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- l... | {"language": "en", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-quality-en-logreg-ft | null | [
"text-classification",
"en",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#text-classification #en #license-mit #region-us
|
# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: English (en)
- model type: logistic regression
- embeddings: fastText embeddings
## How to run
... | [
"# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings",
... | [
"TAGS\n#text-classification #en #license-mit #region-us \n",
"# Multi2ConvAI-Quality: English logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model ty... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned MBert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: English (en)
- model ... | {"language": "en", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Start the program"}]} | inovex/multi2convai-quality-en-mbert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned MBert for English
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: English (en)
- model type: finetuned MBert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface... | [
"# Multi2ConvAI-Quality: finetuned MBert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: English (en)\r\n- model type: finetuned MBert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"##... | [
"TAGS\n#transformers #pytorch #bert #text-classification #en #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned MBert for English \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned Bert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: French (fr)
- model typ... | {"language": "fr", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Lancer le programme"}]} | inovex/multi2convai-quality-fr-bert | null | [
"transformers",
"pytorch",
"safetensors",
"bert",
"text-classification",
"fr",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #safetensors #bert #text-classification #fr #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned Bert for French
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: French (fr)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface Tra... | [
"# Multi2ConvAI-Quality: finetuned Bert for French \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: French (fr)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### Ru... | [
"TAGS\n#transformers #pytorch #safetensors #bert #text-classification #fr #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned Bert for French \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases... |
text-classification | null |
# Multi2ConvAI-Quality: French logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- la... | {"language": "fr", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-quality-fr-logreg-ft | null | [
"text-classification",
"fr",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#text-classification #fr #license-mit #region-us
|
# Multi2ConvAI-Quality: French logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: French (fr)
- model type: logistic regression
- embeddings: fastText embeddings
## How to run
... | [
"# Multi2ConvAI-Quality: French logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: French (fr)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings",
... | [
"TAGS\n#text-classification #fr #license-mit #region-us \n",
"# Multi2ConvAI-Quality: French logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: French (fr)\r\n- model type... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned MBert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: French (fr)
- model ty... | {"language": "fr", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Lancer le programme"}]} | inovex/multi2convai-quality-fr-mbert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"fr",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #bert #text-classification #fr #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned MBert for French
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: French (fr)
- model type: finetuned MBert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface T... | [
"# Multi2ConvAI-Quality: finetuned MBert for French \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: French (fr)\r\n- model type: finetuned MBert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### ... | [
"TAGS\n#transformers #pytorch #bert #text-classification #fr #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned MBert for French \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned Bert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: Italian (it)
- model t... | {"language": "it", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Avviare il programma"}]} | inovex/multi2convai-quality-it-bert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"it",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #bert #text-classification #it #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned Bert for Italian
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: Italian (it)
- model type: finetuned Bert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface T... | [
"# Multi2ConvAI-Quality: finetuned Bert for Italian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: Italian (it)\r\n- model type: finetuned Bert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"### ... | [
"TAGS\n#transformers #pytorch #bert #text-classification #it #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned Bert for Italian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\... |
text-classification | null |
# Multi2ConvAI-Quality: Italian logistic regression model using fasttext embeddings
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- l... | {"language": "it", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Hosted inference API not supported"}]} | inovex/multi2convai-quality-it-logreg-ft | null | [
"text-classification",
"it",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#text-classification #it #license-mit #region-us
|
# Multi2ConvAI-Quality: Italian logistic regression model using fasttext embeddings
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: Italian (ml)
- model type: logistic regression
- embeddings: fastText embeddings
## How to run
... | [
"# Multi2ConvAI-Quality: Italian logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: Italian (ml)\r\n- model type: logistic regression\r\n- embeddings: fastText embeddings",
... | [
"TAGS\n#text-classification #it #license-mit #region-us \n",
"# Multi2ConvAI-Quality: Italian logistic regression model using fasttext embeddings\r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: Italian (ml)\r\n- model ty... |
text-classification | transformers |
# Multi2ConvAI-Quality: finetuned MBert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2convai/en/blog/use-cases), [de](https://multi2convai/en/blog/use-cases)))
- language: Italian (it)
- model ... | {"language": "it", "license": "mit", "tags": ["text-classification"], "widget": [{"text": "Avviare il programma"}]} | inovex/multi2convai-quality-it-mbert | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"it",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #bert #text-classification #it #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Multi2ConvAI-Quality: finetuned MBert for Italian
This model was developed in the Multi2ConvAI project:
- domain: Quality (more details about our use cases: (en, de))
- language: Italian (it)
- model type: finetuned MBert
## How to run
Requires:
- Huggingface transformers
### Run with Huggingface... | [
"# Multi2ConvAI-Quality: finetuned MBert for Italian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))\r\n- language: Italian (it)\r\n- model type: finetuned MBert",
"## How to run\r\n\r\nRequires: \r\n- Huggingface transformers",
"##... | [
"TAGS\n#transformers #pytorch #bert #text-classification #it #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Multi2ConvAI-Quality: finetuned MBert for Italian \r\n\r\nThis model was developed in the Multi2ConvAI project:\r\n- domain: Quality (more details about our use cases: (en, de))... |
text-generation | transformers | hello
| {} | inspectorsolaris/gpt2_french | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| hello
| [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
null | null | hello
| {} | insub/vectorizing_BART | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| hello
| [] | [
"TAGS\n#region-us \n"
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text-generation | null |
# ettengiv DialoGPT Model | {"tags": ["conversational"]} | myynirew/DialoGPT-medium-ettengiv | null | [
"conversational",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#conversational #region-us
|
# ettengiv DialoGPT Model | [
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text-generation | transformers |
# leirbag DialoGPT Model | {"tags": ["conversational"]} | myynirew/DialoGPT-medium-leirbag | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# leirbag DialoGPT Model | [
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] |
text-generation | transformers |
# awazimuruk DialoGPT Model | {"tags": ["conversational"]} | myynirew/DialoGPT-small-awazimuruk | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
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] |
text-generation | transformers | # Sh0rtiAI v2 DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-large-Sh0rtiAI-v2 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Sh0rtiAI v2 DialoGPT Model | [
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] |
text-generation | transformers | # IoniteAI DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-medium-IoniteAI | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # IoniteAI DialoGPT Model | [
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] |
text-generation | transformers | # McKayAI DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-medium-McKayAI-v2 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # McKayAI DialoGPT Model | [
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text-generation | transformers |
# McKayAI DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-medium-McKayAI | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# McKayAI DialoGPT Model | [
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"# McKayAI DialoGPT Model"
] |
text-generation | transformers | # Sh0rtiAI DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-medium-Sh0rtiAI | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Sh0rtiAI DialoGPT Model | [
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"# Sh0rtiAI DialoGPT Model"
] |
text-generation | transformers | # mohnjilesAI DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-medium-mohnjilesAI | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
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"# mohnjilesAI DialoGPT Model"
] |
text-generation | transformers | # orangeAI DialoGPT Model | {"tags": ["conversational"]} | ionite/DialoGPT-medium-orangeAI | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
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] |
text-classification | transformers | ## FinBERT
Code for importing and using this model is available [here](https://github.com/ipuneetrathore/BERT_models)
| {} | ipuneetrathore/bert-base-cased-finetuned-finBERT | null | [
"transformers",
"pytorch",
"jax",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us
| ## FinBERT
Code for importing and using this model is available here
| [
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text-generation | transformers |
#Harry Potter DialoGPT Model | {"tags": ["conversational"]} | ironman123/DialoGPT-small-harrypotter | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
#Harry Potter DialoGPT Model | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-classification | transformers |
# bert-base-uncased finetuned on MNLI
## Model Details and Training Data
We used the pretrained model from [bert-base-uncased](https://huggingface.co/bert-base-uncased) and finetuned it on [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/) dataset.
The training parameters were kept the same as [Devlin et al., 201... | {"language": "en", "tags": ["pytorch", "text-classification"], "datasets": ["MNLI"]} | ishan/bert-base-uncased-mnli | null | [
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"text-classification",
"en",
"dataset:MNLI",
"arxiv:1810.04805",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1810.04805"
] | [
"en"
] | TAGS
#transformers #pytorch #jax #bert #text-classification #en #dataset-MNLI #arxiv-1810.04805 #autotrain_compatible #endpoints_compatible #region-us
| bert-base-uncased finetuned on MNLI
===================================
Model Details and Training Data
-------------------------------
We used the pretrained model from bert-base-uncased and finetuned it on MultiNLI dataset.
The training parameters were kept the same as Devlin et al., 2019 (learning rate = 2e-5,... | [] | [
"TAGS\n#transformers #pytorch #jax #bert #text-classification #en #dataset-MNLI #arxiv-1810.04805 #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-classification | transformers |
# distilbert-base-uncased finetuned on MNLI
## Model Details and Training Data
We used the pretrained model from [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) and finetuned it on [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/) dataset.
The training parameters were kept the same as [... | {"language": "en", "tags": ["pytorch", "text-classification"], "datasets": ["MNLI"]} | ishan/distilbert-base-uncased-mnli | null | [
"transformers",
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"distilbert",
"text-classification",
"en",
"dataset:MNLI",
"arxiv:1810.04805",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1810.04805"
] | [
"en"
] | TAGS
#transformers #pytorch #distilbert #text-classification #en #dataset-MNLI #arxiv-1810.04805 #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased finetuned on MNLI
=========================================
Model Details and Training Data
-------------------------------
We used the pretrained model from distilbert-base-uncased and finetuned it on MultiNLI dataset.
The training parameters were kept the same as Devlin et al., 2019 (lea... | [] | [
"TAGS\n#transformers #pytorch #distilbert #text-classification #en #dataset-MNLI #arxiv-1810.04805 #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
# Hrry Potter DialoGPT Model
| {"tags": ["conversational"]} | ishraaqparvez/DialoGPT-small-harrypotter | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Hrry Potter DialoGPT Model
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] |
text-classification | transformers | Este es el primer modelo de prueba BETO_3D | {} | ismaelardo/BETO_3d | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us
| Este es el primer modelo de prueba BETO_3D | [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
# GTP2-Poems Generator, English
This model is part of the Poems+AI experiment
more info https://poems-ai.github.io/art/
# Original Dataset
- https://www.kaggle.com/michaelarman/poemsdataset
- Marcos de la Fuente's poems
| {"language": "en", "license": "mit", "tags": ["GPT"]} | ismaelfaro/gpt2-poems.en | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"GPT",
"en",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #GPT #en #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# GTP2-Poems Generator, English
This model is part of the Poems+AI experiment
more info URL
# Original Dataset
- URL
- Marcos de la Fuente's poems
| [
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text-generation | transformers |
# GTP2-Poems Spanish
This model is part of the Poems+AI experiment
more info https://poems-ai.github.io/art/
# Original Dataset
- https://www.kaggle.com/andreamorgar/spanish-poetry-dataset
- Marcos de la Fuente's poems
| {"language": "es", "license": "mit", "tags": ["GPT"]} | ismaelfaro/gpt2-poems.es | null | [
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"text-generation",
"GPT",
"es",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #GPT #es #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# GTP2-Poems Spanish
This model is part of the Poems+AI experiment
more info URL
# Original Dataset
- URL
- Marcos de la Fuente's poems
| [
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-cats-vs-dogs
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vi... | {"license": "apache-2.0", "tags": ["image-classification", "generated_from_trainer"], "datasets": ["cats_vs_dogs"], "metrics": ["accuracy"], "model-index": [{"name": "vit-base-cats-vs-dogs", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "cats_vs_dogs", "type"... | ismgar01/vit-base-cats-vs-dogs | null | [
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"dataset:cats_vs_dogs",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #vit #image-classification #generated_from_trainer #dataset-cats_vs_dogs #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| vit-base-cats-vs-dogs
=====================
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cats\_vs\_dogs dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0182
* Accuracy: 0.9937
Model description
-----------------
More information needed
Intended use... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 32\n* seed: 1337\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 5.0\n* mixed\\... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.... |
text2text-generation | transformers |
# IT5 Base for Formal-to-informal Style Transfer ๐ค
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to-te... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Questa performance \u00e8 a dir poco spiacevole."}, {"text": "In attesa di un Suo cortese ris... | it5/it5-base-formal-to-informal | null | [
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"autotrain_compatible",
"endpoints_compati... | null | 2022-03-02T23:29:05+00:00 | [
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|
# IT5 Base for Formal-to-informal Style Transfer
This repository contains the checkpoint for the IT5 Base model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understan... | [
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"# IT5 B... |
text2text-generation | transformers | # IT5 Base for News Headline Generation ๐๏ธ ๐ฎ๐น
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper [IT5: Large-scale Text-to-text Pretraining for Itali... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "headline-generation"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa deg... | it5/it5-base-headline-generation | null | [
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"arxiv:2203.03759",
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"autotrain_compatible"... | null | 2022-03-02T23:29:05+00:00 | [
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| # IT5 Base for News Headline Generation ๏ธ ๐ฎ๐น
This repository contains the checkpoint for the IT5 Base model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by G... | [
"# IT5 Base for News Headline Generation ๏ธ ๐ฎ๐น\n\nThis repository contains the checkpoint for the IT5 Base model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generati... | [
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text2text-generation | transformers | # IT5 Base for News Headline Style Transfer (Il Giornale to Repubblica) ๐๏ธโก๏ธ๐๏ธ ๐ฎ๐น
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part o... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/it5-base-ilgiornale-to-repubblica | null | [
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"... | null | 2022-03-02T23:29:05+00:00 | [
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| # IT5 Base for News Headline Style Transfer (Il Giornale to Repubblica) ๏ธ๏ธ๏ธ ๐ฎ๐น
This repository contains the checkpoint for the IT5 Base model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-scale... | [
"# IT5 Base for News Headline Style Transfer (Il Giornale to Repubblica) ๏ธ๏ธ๏ธ ๐ฎ๐น\n\nThis repository contains the checkpoint for the IT5 Base model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Larg... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #italian #sequence-to-sequence #newspaper #ilgiornale #repubblica #style-transfer #it #dataset-gsarti/change_it #arxiv-2203.03759 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
... |
text2text-generation | transformers |
# IT5 Base for Informal-to-formal Style Transfer ๐ง
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to-te... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "maronn qualcuno mi spieg' CHECCOSA SUCCEDE?!?!"}, {"text": "wellaaaaaaa, ma frat\u00e9 sei pr... | it5/it5-base-informal-to-formal | null | [
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|
# IT5 Base for Informal-to-formal Style Transfer
This repository contains the checkpoint for the IT5 Base model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understan... | [
"# IT5 Base for Informal-to-formal Style Transfer \n\nThis repository contains the checkpoint for the IT5 Base model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Und... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #italian #sequence-to-sequence #style-transfer #formality-style-transfer #it #dataset-yahoo/xformal_it #arxiv-2203.03759 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# IT5 B... |
summarization | transformers | # IT5 Base for News Summarization โ๏ธ๐๏ธ ๐ฎ๐น
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on news summarization on the [Fanpage](https://huggingface.co/datasets/ARTeLab/fanpage) and [Il Post](https://huggingface.co/datasets/ARTeLab/ilpost) corpora ... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "fanpage", "ilpost", "summarization"], "datasets": ["ARTeLab/fanpage", "ARTeLab/ilpost"], "metrics": ["rouge"], "widget": [{"text": "Non lo vuole sposare. E\u2019 quanto emerge all\u2019interno dell\u2019ultima intervista di Raffa... | it5/it5-base-news-summarization | null | [
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"co2_e... | null | 2022-03-02T23:29:05+00:00 | [
"2203.03759"
] | [
"it"
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#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #italian #sequence-to-sequence #fanpage #ilpost #summarization #it #dataset-ARTeLab/fanpage #dataset-ARTeLab/ilpost #arxiv-2203.03759 #license-apache-2.0 #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_space #tex... | # IT5 Base for News Summarization ๏ธ๏ธ ๐ฎ๐น
This repository contains the checkpoint for the IT5 Base model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sa... | [
"# IT5 Base for News Summarization ๏ธ๏ธ ๐ฎ๐น\n\nThis repository contains the checkpoint for the IT5 Base model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabr... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #italian #sequence-to-sequence #fanpage #ilpost #summarization #it #dataset-ARTeLab/fanpage #dataset-ARTeLab/ilpost #arxiv-2203.03759 #license-apache-2.0 #model-index #co2_eq_emissions #autotrain_compatible #endpoints_compatible #has_spac... |
text2text-generation | transformers | # IT5 Base for Question Answering โ๏ธ ๐ฎ๐น
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on extractive question answering on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Tex... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "squad_it", "text2text-question-answering", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["f1", "exact-match"], "widget": [{"text": "In seguito all' evento di estinzione del Cretaceo-Paleogene, l' estinzione dei d... | it5/it5-base-question-answering | null | [
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"autotrain_compatible",
"endpoints_... | null | 2022-03-02T23:29:05+00:00 | [
"2203.03759"
] | [
"it"
] | TAGS
#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #italian #sequence-to-sequence #squad_it #text2text-question-answering #it #dataset-squad_it #arxiv-2203.03759 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| # IT5 Base for Question Answering โ๏ธ ๐ฎ๐น
This repository contains the checkpoint for the IT5 Base model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sar... | [
"# IT5 Base for Question Answering โ๏ธ ๐ฎ๐น\n\nThis repository contains the checkpoint for the IT5 Base model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabri... | [
"TAGS\n#transformers #pytorch #tf #jax #tensorboard #t5 #text2text-generation #italian #sequence-to-sequence #squad_it #text2text-question-answering #it #dataset-squad_it #arxiv-2203.03759 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \... |
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