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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bart-JES-cnn_dailymail
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) o... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"]} | jogonba2/bart-JES-cnn_dailymail | null | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| bart-JES-cnn\_dailymail
=======================
This model is a fine-tuned version of facebook/bart-large on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1452
* Rouge1: 43.9753
* Rouge2: 19.7191
* Rougel: 33.6236
* Rougelsum: 41.1683
* Gen Len: 80.1767
Model description
-... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 6.0\n* mixed\\_prec... | [
"TAGS\n#transformers #pytorch #bart #text2text-generation #generated_from_trainer #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\... |
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. -->
# barthez-deft-archeologie
This model is a fine-tuned version of [moussaKam/barthez](https://huggingface.co/moussaKam/barthez) on ... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"]} | jogonba2/barthez-deft-archeologie | null | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| barthez-deft-archeologie
========================
This model is a fine-tuned version of moussaKam/barthez on an unknown dataset.
Note: this model is one of the preliminary experiments and it underperforms the models published in the paper (using MBartHez and HAL/Wiki pre-training + copy mechanisms)
It achieves th... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20.0\n* mixed\\_pre... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch... |
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. -->
# barthez-deft-chimie
This model is a fine-tuned version of [moussaKam/barthez](https://huggingface.co/moussaKam/barthez) on an un... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"]} | jogonba2/barthez-deft-chimie | null | [
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"pytorch",
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"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| barthez-deft-chimie
===================
This model is a fine-tuned version of moussaKam/barthez on an unknown dataset.
Note: this model is one of the preliminary experiments and it underperforms the models published in the paper (using MBartHez and HAL/Wiki pre-training + copy mechanisms)
It achieves the followin... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20.0\n* mixed\\_pre... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch... |
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. -->
# barthez-deft-linguistique
This model is a fine-tuned version of [moussaKam/barthez](https://huggingface.co/moussaKam/barthez) on... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"]} | jogonba2/barthez-deft-linguistique | null | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| barthez-deft-linguistique
=========================
This model is a fine-tuned version of moussaKam/barthez on an unknown dataset.
Note: this model is one of the preliminary experiments and it underperforms the models published in the paper (using MBartHez and HAL/Wiki pre-training + copy mechanisms)
It achieves ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20.0\n* mixed\\_pre... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch... |
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. -->
# barthez-deft-sciences_de_l_information
This model is a fine-tuned version of [moussaKam/barthez](https://huggingface.co/moussaKa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"]} | jogonba2/barthez-deft-sciences_de_l_information | null | [
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"text2text-generation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| barthez-deft-sciences\_de\_l\_information
=========================================
This model is a fine-tuned version of moussaKam/barthez on an unknown dataset.
Note: this model is one of the preliminary experiments and it underperforms the models published in the paper (using MBartHez and HAL/Wiki pre-training +... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 4\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 20.0\n* mixed\\_pre... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch... |
null | 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. -->
# mbarthez-davide_articles-copy_enhanced
This model is a fine-tuned version of [moussaKam/mbarthez](https://huggingface.co/moussaK... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"]} | jogonba2/mbarthez-copy_mechanism-hal_articles | null | [
"transformers",
"pytorch",
"mbart",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #mbart #generated_from_trainer #license-apache-2.0 #model-index #endpoints_compatible #region-us
| mbarthez-davide\_articles-copy\_enhanced
========================================
This model is a fine-tuned version of moussaKam/mbarthez on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4905
* Rouge1: 36.548
* Rouge2: 19.6282
* Rougel: 30.2513
* Rougelsum: 30.2765
* Gen Le... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3.0\n* mixed\\_prec... | [
"TAGS\n#transformers #pytorch #mbart #generated_from_trainer #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed... |
text-generation | transformers |
# Arya DialoGPT Model | {"tags": ["conversational"]} | jogp10/DialoGPT-medium-arya | 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
|
# Arya DialoGPT Model | [
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] |
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. -->
#
This model is a fine-tuned version of [hf-test/xls-r-dummy](https://huggingface.co/hf-test/xls-r-dummy) on the MOZILLA-FOUNDATI... | {"language": ["ab"], "tags": ["automatic-speech-recognition", "mozilla-foundation/common_voice_7_0", "generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "", "results": []}]} | joheras/xls-r-ab-spanish | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"ab",
"dataset:common_voice",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ab"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ab #dataset-common_voice #endpoints_compatible #region-us
|
#
This model is a fine-tuned version of hf-test/xls-r-dummy on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 156.8790
- Wer: 1.3448
## Model description
More information needed
## Intended uses & limitations
More information needed
## Tr... | [
"# \n\nThis model is a fine-tuned version of hf-test/xls-r-dummy on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AB dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 156.8790\n- Wer: 1.3448",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore inform... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #mozilla-foundation/common_voice_7_0 #generated_from_trainer #ab #dataset-common_voice #endpoints_compatible #region-us \n",
"# \n\nThis model is a fine-tuned version of hf-test/xls-r-dummy on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - AB datase... |
sentence-similarity | sentence-transformers |
# DeCLUTR-base
## Model description
The "DeCLUTR-base" model from our paper: [DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations](https://arxiv.org/abs/2006.03659).
## Intended uses & limitations
The model is intended to be used as a universal sentence encoder, similar to [Google's Univers... | {"language": "en", "license": "apache-2.0", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "datasets": ["openwebtext"], "pipeline_tag": "sentence-similarity"} | johngiorgi/declutr-base | null | [
"sentence-transformers",
"pytorch",
"jax",
"roberta",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:openwebtext",
"arxiv:2006.03659",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2006.03659"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #jax #roberta #feature-extraction #sentence-similarity #en #dataset-openwebtext #arxiv-2006.03659 #license-apache-2.0 #endpoints_compatible #region-us
|
# DeCLUTR-base
## Model description
The "DeCLUTR-base" model from our paper: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations.
## Intended uses & limitations
The model is intended to be used as a universal sentence encoder, similar to Google's Universal Sentence Encoder or Sentence Trans... | [
"# DeCLUTR-base",
"## Model description\n\nThe \"DeCLUTR-base\" model from our paper: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations.",
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"# DeCLUTR-base",
"## Model description\n\nThe \"DeCLUTR-base\" model from our paper: DeCLUTR: Deep Contrastive Learn... |
sentence-similarity | sentence-transformers |
# DeCLUTR-sci-base
## Model description
This is the [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) model, with extended pretraining on over 2 million scientific papers from [S2ORC](https://github.com/allenai/s2orc/) using the self-supervised training strategy presented in... | {"language": "en", "license": "apache-2.0", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "datasets": ["s2orc"], "pipeline_tag": "sentence-similarity"} | johngiorgi/declutr-sci-base | null | [
"sentence-transformers",
"pytorch",
"jax",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:s2orc",
"arxiv:2006.03659",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2006.03659"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #jax #bert #feature-extraction #sentence-similarity #en #dataset-s2orc #arxiv-2006.03659 #license-apache-2.0 #endpoints_compatible #region-us
|
# DeCLUTR-sci-base
## Model description
This is the allenai/scibert_scivocab_uncased model, with extended pretraining on over 2 million scientific papers from S2ORC using the self-supervised training strategy presented in DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations.
## Intended uses ... | [
"# DeCLUTR-sci-base",
"## Model description\n\nThis is the allenai/scibert_scivocab_uncased model, with extended pretraining on over 2 million scientific papers from S2ORC using the self-supervised training strategy presented in DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations.",
"## ... | [
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"# DeCLUTR-sci-base",
"## Model description\n\nThis is the allenai/scibert_scivocab_uncased model, with extended pretraining o... |
sentence-similarity | sentence-transformers |
# DeCLUTR-small
## Model description
The "DeCLUTR-small" model from our paper: [DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations](https://arxiv.org/abs/2006.03659).
## Intended uses & limitations
The model is intended to be used as a universal sentence encoder, similar to [Google's Univ... | {"language": "en", "license": "apache-2.0", "tags": ["sentence-transformers", "feature-extraction", "sentence-similarity"], "datasets": ["openwebtext"], "pipeline_tag": "sentence-similarity"} | johngiorgi/declutr-small | null | [
"sentence-transformers",
"pytorch",
"jax",
"roberta",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:openwebtext",
"arxiv:2006.03659",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2006.03659"
] | [
"en"
] | TAGS
#sentence-transformers #pytorch #jax #roberta #feature-extraction #sentence-similarity #en #dataset-openwebtext #arxiv-2006.03659 #license-apache-2.0 #endpoints_compatible #region-us
|
# DeCLUTR-small
## Model description
The "DeCLUTR-small" model from our paper: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations.
## Intended uses & limitations
The model is intended to be used as a universal sentence encoder, similar to Google's Universal Sentence Encoder or Sentence Tr... | [
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"## Model description\n\nThe \"DeCLUTR-small\" model from our paper: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations.",
"## Intended uses & limitations\n\nThe model is intended to be used as a universal sentence encoder, similar to Google's Universal Sentence Encod... | [
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"# DeCLUTR-small",
"## Model description\n\nThe \"DeCLUTR-small\" model from our paper: DeCLUTR: Deep Contrastive Lea... |
text-generation | transformers | ## GPT-2 for Skript
## Complete your Skript automatically via a finetuned GPT-2 model
`0.57` Training loss on about 2 epochs (in total)
1.2 million lines of Skript is inside the dataset.
Inference Colab: https://colab.research.google.com/drive/1ujtLt7MOk7Nsag3q-BYK62Kpoe4Lr4PE | {} | johnpaulbin/gpt2-skript-1m-v5 | null | [
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"safetensors",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| ## GPT-2 for Skript
## Complete your Skript automatically via a finetuned GPT-2 model
'0.57' Training loss on about 2 epochs (in total)
1.2 million lines of Skript is inside the dataset.
Inference Colab: URL | [
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text-generation | transformers | GPT-2 Skript 80k lines. v3
Training loss: `0.594200`
1.5 GB
Inferencing colab: https://colab.research.google.com/drive/1uTAPLa1tuNXFpG0qVLSseMro6iU9-xNc | {} | johnpaulbin/gpt2-skript-80-v3 | 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
| GPT-2 Skript 80k lines. v3
Training loss: '0.594200'
1.5 GB
Inferencing colab: URL | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers | GPT-2 for the Minecraft Plugin: Skript (80,000 Lines, 3< GB: GPT-2 Large model finetune)
Inferencing Colab: https://colab.research.google.com/drive/1uTAPLa1tuNXFpG0qVLSseMro6iU9-xNc | {} | johnpaulbin/gpt2-skript-80 | null | [
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"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
| GPT-2 for the Minecraft Plugin: Skript (80,000 Lines, 3< GB: GPT-2 Large model finetune)
Inferencing Colab: URL | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers | GPT2 for Minecraft Plugin Skript (50,000 Lines, 3 GB: GPT-Large model finetune)
Inference Colab: https://colab.research.google.com/drive/1z8dwtNP8Kj3evEOmKmGBHK_vmP30lgiY | {} | johnpaulbin/gpt2-skript-base | null | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| GPT2 for Minecraft Plugin Skript (50,000 Lines, 3 GB: GPT-Large model finetune)
Inference Colab: URL | [] | [
"TAGS\n#transformers #pytorch #safetensors #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers | Trained on ~400 youtube titles of meme compilations on youtube.
WARNING: may produce offensive content. | {} | johnpaulbin/meme-titles | null | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Trained on ~400 youtube titles of meme compilations on youtube.
WARNING: may produce offensive content. | [] | [
"TAGS\n#transformers #pytorch #safetensors #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
# Monkey D Luffy DialoGPT Model | {"tags": ["conversational"]} | jollmimmim/DialoGPT-small-monkeydluffy | 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
|
# Monkey D Luffy DialoGPT Model | [
"# Monkey D Luffy DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Monkey D Luffy DialoGPT Model"
] |
text2text-generation | transformers | Just a test
| {} | jonatasgrosman/bartuque-bart-base-pretrained-mm-2 | null | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us
| Just a test
| [] | [
"TAGS\n#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text2text-generation | transformers | Just a test
| {} | jonatasgrosman/bartuque-bart-base-pretrained-r-2 | null | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us
| Just a test
| [] | [
"TAGS\n#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text2text-generation | transformers | Just a test
| {} | jonatasgrosman/bartuque-bart-base-pretrained-rm-2 | null | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us
| Just a test
| [] | [
"TAGS\n#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text2text-generation | transformers | Just a test
| {} | jonatasgrosman/bartuque-bart-base-random-r-2 | null | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us
| Just a test
| [] | [
"TAGS\n#transformers #pytorch #bart #text2text-generation #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers | testing
| {} | jonatasgrosman/paraphrase | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| testing
| [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned wav2vec2 large model for speech recognition in English
Fine-tuned [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on English using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure that your spee... | {"language": "en", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "Wav2Vec2 English by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition", "name":... | jonatasgrosman/wav2vec2-large-english | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"en",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #en #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
| Fine-tuned wav2vec2 large model for speech recognition in English
=================================================================
Fine-tuned facebook/wav2vec2-large on English using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz.
Th... | [] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #en #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned French Voxpopuli wav2vec2 large model for speech recognition in French
Fine-tuned [facebook/wav2vec2-large-fr-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-fr-voxpopuli) on French using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When u... | {"language": "fr", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "Voxpopuli Wav2Vec2 French by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition"... | jonatasgrosman/wav2vec2-large-fr-voxpopuli-french | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"fr",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #fr #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
| Fine-tuned French Voxpopuli wav2vec2 large model for speech recognition in French
=================================================================================
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli on French using the train and validation splits of Common Voice 6.1.
When using this model, make sure that... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #fr #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Arabic
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Arabic using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice) and [Arabic Speech Corpus](https://... | {"language": "ar", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "arabic_speech_corpus"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Arabic by Jonatas Grosman", "results": [{"task": {"type": "automatic-... | jonatasgrosman/wav2vec2-large-xlsr-53-arabic | null | [
"transformers",
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"wav2vec2",
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"audio",
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"xlsr-fine-tuning-week",
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"dataset:arabic_speech_corpus",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ar"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #ar #dataset-common_voice #dataset-arabic_speech_corpus #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Arabic
===============================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Arabic using the train and validation splits of Common Voice 6.1 and Arabic Speech Corpus.
When using this model, make sure that your speech inp... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #ar #dataset-common_voice #dataset-arabic_speech_corpus #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Chinese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Chinese using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice), [CSS10](https://github.com/Kyuby... | {"language": "zh", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Chinese (zh-CN) by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognit... | jonatasgrosman/wav2vec2-large-xlsr-53-chinese-zh-cn | null | [
"transformers",
"pytorch",
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"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"zh",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #zh #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Chinese
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Chinese using the train and validation splits of Common Voice 6.1, CSS10 and ST-CMDS.
When using this model, make sure that your speech input ... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #zh #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Dutch
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Dutch using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice) and [CSS10](https://github.com/Kyubyo... | {"language": "nl", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "nl", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-dutch | null | [
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"wav2vec2",
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"nl",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"doi:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"nl"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #nl #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #doi-10.57967/hf/0203 #license-apache-2.0 #model-index #endp... | Fine-tuned XLSR-53 large model for speech recognition in Dutch
==============================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Dutch using the train and validation splits of Common Voice 6.1 and CSS10.
When using this model, make sure that your speech input is sampled at 1... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #nl #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #doi-10.57967/hf/0203 #license-apache-2.0 #model-index... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in English
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on English using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure... | {"language": "en", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "en", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-english | null | [
"transformers",
"pytorch",
"jax",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"en",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_vo... | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #safetensors #wav2vec2 #automatic-speech-recognition #audio #en #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_com... | Fine-tuned XLSR-53 large model for speech recognition in English
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on English using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz... | [] | [
"TAGS\n#transformers #pytorch #jax #safetensors #wav2vec2 #automatic-speech-recognition #audio #en #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoin... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Finnish
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Finnish using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice) and [CSS10](https://github.com/Ky... | {"language": "fi", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Finnish by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition", "n... | jonatasgrosman/wav2vec2-large-xlsr-53-finnish | null | [
"transformers",
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"automatic-speech-recognition",
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"xlsr-fine-tuning-week",
"fi",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fi"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #fi #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Finnish
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Finnish using the train and validation splits of Common Voice 6.1 and CSS10.
When using this model, make sure that your speech input is sample... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #fi #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in French
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on French using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure t... | {"language": "fr", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "fr", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-french | null | [
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"jax",
"wav2vec2",
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"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #fr #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in French
===============================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on French using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz.
... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #fr #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in German
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on German using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure t... | {"language": "de", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "de", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-german | null | [
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"de",
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"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #de #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in German
===============================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on German using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz.
... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #de #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Greek
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Greek using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice) and [CSS10](https://github.com/Kyubyo... | {"language": "el", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Greek by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition", "nam... | jonatasgrosman/wav2vec2-large-xlsr-53-greek | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"el",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"el"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #el #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Greek
==============================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Greek using the train and validation splits of Common Voice 6.1 and CSS10.
When using this model, make sure that your speech input is sampled at 1... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #el #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Hungarian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Hungarian using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice) and [CSS10](https://github.co... | {"language": "hu", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Hungarian by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition", ... | jonatasgrosman/wav2vec2-large-xlsr-53-hungarian | null | [
"transformers",
"pytorch",
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"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"hu",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"hu"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #hu #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Hungarian
==================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Hungarian using the train and validation splits of Common Voice 6.1 and CSS10.
When using this model, make sure that your speech input is ... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #hu #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Italian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Italian using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure... | {"language": "it", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "it", "mozilla-foundation/common_voice_6_0", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-italian | null | [
"transformers",
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"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"it",
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"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #it #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in Italian
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Italian using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #it #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Japanese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Japanese using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice), [CSS10](https://github.com/Kyu... | {"language": "ja", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Japanese by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition", "... | jonatasgrosman/wav2vec2-large-xlsr-53-japanese | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"ja",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"ja"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #ja #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Japanese
=================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Japanese using the train and validation splits of Common Voice 6.1, CSS10 and JSUT.
When using this model, make sure that your speech input ... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #ja #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Persian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Persian using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure... | {"language": "fa", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "metrics": ["wer", "cer"], "model-index": [{"name": "XLSR Wav2Vec2 Persian by Jonatas Grosman", "results": [{"task": {"type": "automatic-speech-recognition", "n... | jonatasgrosman/wav2vec2-large-xlsr-53-persian | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"fa",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #fa #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
| Fine-tuned XLSR-53 large model for speech recognition in Persian
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Persian using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #fa #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n"
] |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Polish
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Polish using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure t... | {"language": "pl", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "pl", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-polish | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"pl",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"pl"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #pl #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in Polish
===============================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Polish using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz.
... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #pl #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Portuguese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Portuguese using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, mak... | {"language": "pt", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "pt", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-portuguese | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"pt",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #pt #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in Portuguese
===================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #pt #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Russian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Russian using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice) and [CSS10](https://github.com/Ky... | {"language": "ru", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "robust-speech-event", "ru", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-russian | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"ru",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #ru #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in Russian
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Russian using the train and validation splits of Common Voice 6.1 and CSS10.
When using this model, make sure that your speech input is sample... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #ru #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLSR-53 large model for speech recognition in Spanish
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Spanish using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
When using this model, make sure... | {"language": "es", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "es", "hf-asr-leaderboard", "mozilla-foundation/common_voice_6_0", "robust-speech-event", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice", "mozilla-foundation/common_voice_6_0"], "metrics": ["wer", "cer"], "mod... | jonatasgrosman/wav2vec2-large-xlsr-53-spanish | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"es",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"lice... | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #es #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible #has_... | Fine-tuned XLSR-53 large model for speech recognition in Spanish
================================================================
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Spanish using the train and validation splits of Common Voice 6.1.
When using this model, make sure that your speech input is sampled at 16kHz... | [] | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #es #hf-asr-leaderboard #mozilla-foundation/common_voice_6_0 #robust-speech-event #speech #xlsr-fine-tuning-week #dataset-common_voice #dataset-mozilla-foundation/common_voice_6_0 #license-apache-2.0 #model-index #endpoints_compatible... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in Dutch
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Dutch using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Multilingual LibriSpeech](h... | {"language": ["nl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "nl", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 Dutch by Jonatas Grosman", "results": [{"task": ... | jonatasgrosman/wav2vec2-xls-r-1b-dutch | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"nl",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"nl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #nl #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in Dutch
Fine-tuned facebook/wav2vec2-xls-r-1b on Dutch using the train and validation splits of Common Voice 8.0, Multilingual LibriSpeech, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by... | [
"# Fine-tuned XLS-R 1B model for speech recognition in Dutch\n\nFine-tuned facebook/wav2vec2-xls-r-1b on Dutch using the train and validation splits of Common Voice 8.0, Multilingual LibriSpeech, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #nl #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in English
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on English using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Multilingual LibriSpeec... | {"language": ["en"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "en", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 English by Jonatas Grosman", "results": [{"task"... | jonatasgrosman/wav2vec2-xls-r-1b-english | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in English
Fine-tuned facebook/wav2vec2-xls-r-1b on English using the train and validation splits of Common Voice 8.0, Multilingual LibriSpeech, TED-LIUMv3, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz.
This model has be... | [
"# Fine-tuned XLS-R 1B model for speech recognition in English\n\nFine-tuned facebook/wav2vec2-xls-r-1b on English using the train and validation splits of Common Voice 8.0, Multilingual LibriSpeech, TED-LIUMv3, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis mod... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #en #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in French
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on French using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [MediaSpeech](https://www.... | {"language": ["fr"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "fr", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 French by Jonatas Grosman", "results": [{"task":... | jonatasgrosman/wav2vec2-xls-r-1b-french | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"fr"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fr #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in French
Fine-tuned facebook/wav2vec2-xls-r-1b on French using the train and validation splits of Common Voice 8.0, MediaSpeech, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz.
... | [
"# Fine-tuned XLS-R 1B model for speech recognition in French\n\nFine-tuned facebook/wav2vec2-xls-r-1b on French using the train and validation splits of Common Voice 8.0, MediaSpeech, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled at ... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #fr #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in German
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on German using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Multilingual TEDx](http:/... | {"language": ["de"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "de", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 German by Jonatas Grosman", "results": [{"task":... | jonatasgrosman/wav2vec2-xls-r-1b-german | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #de #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in German
Fine-tuned facebook/wav2vec2-xls-r-1b on German using the train and validation splits of Common Voice 8.0, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz.
This model h... | [
"# Fine-tuned XLS-R 1B model for speech recognition in German\n\nFine-tuned facebook/wav2vec2-xls-r-1b on German using the train and validation splits of Common Voice 8.0, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThi... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #de #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in Italian
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Italian using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Multilingual TEDx](http... | {"language": ["it"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "it", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 Italian by Jonatas Grosman", "results": [{"task"... | jonatasgrosman/wav2vec2-xls-r-1b-italian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"it",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #it #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in Italian
Fine-tuned facebook/wav2vec2-xls-r-1b on Italian using the train and validation splits of Common Voice 8.0, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz.
This model... | [
"# Fine-tuned XLS-R 1B model for speech recognition in Italian\n\nFine-tuned facebook/wav2vec2-xls-r-1b on Italian using the train and validation splits of Common Voice 8.0, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nT... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #it #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in Polish
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Polish using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Multilingual LibriSpeech]... | {"language": ["pl"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "pl", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 Polish by Jonatas Grosman", "results": [{"task":... | jonatasgrosman/wav2vec2-xls-r-1b-polish | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"pl",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"pl"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #pl #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in Polish
Fine-tuned facebook/wav2vec2-xls-r-1b on Polish using the train and validation splits of Common Voice 8.0, Multilingual LibriSpeech, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned ... | [
"# Fine-tuned XLS-R 1B model for speech recognition in Polish\n\nFine-tuned facebook/wav2vec2-xls-r-1b on Polish using the train and validation splits of Common Voice 8.0, Multilingual LibriSpeech, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fi... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #pl #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in Portuguese
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Portuguese using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [CORAA](https://gi... | {"language": ["pt"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "pt", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 Portuguese by Jonatas Grosman", "results": [{"ta... | jonatasgrosman/wav2vec2-xls-r-1b-portuguese | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"pt",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #pt #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in Portuguese
Fine-tuned facebook/wav2vec2-xls-r-1b on Portuguese using the train and validation splits of Common Voice 8.0, CORAA, Multilingual TEDx, and Multilingual LibriSpeech.
When using this model, make sure that your speech input is sampled at 16kHz.
This mod... | [
"# Fine-tuned XLS-R 1B model for speech recognition in Portuguese\n\nFine-tuned facebook/wav2vec2-xls-r-1b on Portuguese using the train and validation splits of Common Voice 8.0, CORAA, Multilingual TEDx, and Multilingual LibriSpeech.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #pt #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in Russian
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Russian using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [Golos](https://www.open... | {"language": ["ru"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "ru"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 Russian by Jonatas Grosman", "results": [{"task"... | jonatasgrosman/wav2vec2-xls-r-1b-russian | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"ru",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"ru"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #ru #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in Russian
Fine-tuned facebook/wav2vec2-xls-r-1b on Russian using the train and validation splits of Common Voice 8.0, Golos, and Multilingual TEDx.
When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the Hu... | [
"# Fine-tuned XLS-R 1B model for speech recognition in Russian\n\nFine-tuned facebook/wav2vec2-xls-r-1b on Russian using the train and validation splits of Common Voice 8.0, Golos, and Multilingual TEDx.\nWhen using this model, make sure that your speech input is sampled at 16kHz.\n\nThis model has been fine-tuned ... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #ru #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
automatic-speech-recognition | transformers |
# Fine-tuned XLS-R 1B model for speech recognition in Spanish
Fine-tuned [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on Spanish using the train and validation splits of [Common Voice 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0), [MediaSpeech](https://ww... | {"language": ["es"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "es", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R Wav2Vec2 Spanish by Jonatas Grosman", "results": [{"task"... | jonatasgrosman/wav2vec2-xls-r-1b-spanish | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"has_space",
"region:... | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us
|
# Fine-tuned XLS-R 1B model for speech recognition in Spanish
Fine-tuned facebook/wav2vec2-xls-r-1b on Spanish using the train and validation splits of Common Voice 8.0, MediaSpeech, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.
When using this model, make sure that your speech input is sampled at 16kHz... | [
"# Fine-tuned XLS-R 1B model for speech recognition in Spanish\n\nFine-tuned facebook/wav2vec2-xls-r-1b on Spanish using the train and validation splits of Common Voice 8.0, MediaSpeech, Multilingual TEDx, Multilingual LibriSpeech, and Voxpopuli.\nWhen using this model, make sure that your speech input is sampled a... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #es #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us \n",
"# Fine-tuned XLS-R 1B model for sp... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion... | jonc/distilbert-base-uncased-finetuned-emotion | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-emotion
=========================================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2159
* Accuracy: 0.923
* F1: 0.9231
Model description
-----------------
Mor... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learn... |
feature-extraction | transformers |
# Icelandic ConvBERT-Base
This model was pretrained on the [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/), which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.
# Acknowledgments
This research was supported with Cloud TPUs fr... | {"language": ["is"], "license": "cc-by-4.0", "datasets": ["igc"]} | jonfd/convbert-base-igc-is | null | [
"transformers",
"pytorch",
"tf",
"convbert",
"feature-extraction",
"is",
"dataset:igc",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is"
] | TAGS
#transformers #pytorch #tf #convbert #feature-extraction #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us
|
# Icelandic ConvBERT-Base
This model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.
# Acknowledgments
This research was supported with Cloud TPUs from Google's TPU Research Cloud... | [
"# Icelandic ConvBERT-Base\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.",
"# Acknowledgments\nThis research was supported with Cloud TPUs from Google's TPU Rese... | [
"TAGS\n#transformers #pytorch #tf #convbert #feature-extraction #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us \n",
"# Icelandic ConvBERT-Base\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a Word... |
feature-extraction | transformers |
# Icelandic ConvBERT-Small
This model was pretrained on the [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/), which contains approximately 1.69B tokens, using default settings. The model uses a Unigram tokenizer with a vocabulary size of 96,000.
# Acknowledgments
This research was supported with Cloud TPUs fro... | {"language": ["is"], "license": "cc-by-4.0", "datasets": ["igc"]} | jonfd/convbert-small-igc-is | null | [
"transformers",
"pytorch",
"tf",
"convbert",
"feature-extraction",
"is",
"dataset:igc",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is"
] | TAGS
#transformers #pytorch #tf #convbert #feature-extraction #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us
|
# Icelandic ConvBERT-Small
This model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a Unigram tokenizer with a vocabulary size of 96,000.
# Acknowledgments
This research was supported with Cloud TPUs from Google's TPU Research Cloud ... | [
"# Icelandic ConvBERT-Small\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a Unigram tokenizer with a vocabulary size of 96,000.",
"# Acknowledgments\nThis research was supported with Cloud TPUs from Google's TPU Resea... | [
"TAGS\n#transformers #pytorch #tf #convbert #feature-extraction #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us \n",
"# Icelandic ConvBERT-Small\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a Uni... |
null | transformers |
# Icelandic ELECTRA-Base
This model was pretrained on the [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/), which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.
# Acknowledgments
This research was supported with Cloud TPUs fro... | {"language": ["is"], "license": "cc-by-4.0", "datasets": ["igc"]} | jonfd/electra-base-igc-is | null | [
"transformers",
"pytorch",
"electra",
"pretraining",
"is",
"dataset:igc",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is"
] | TAGS
#transformers #pytorch #electra #pretraining #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us
|
# Icelandic ELECTRA-Base
This model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.
# Acknowledgments
This research was supported with Cloud TPUs from Google's TPU Research Cloud ... | [
"# Icelandic ELECTRA-Base\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.",
"# Acknowledgments\nThis research was supported with Cloud TPUs from Google's TPU Resea... | [
"TAGS\n#transformers #pytorch #electra #pretraining #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us \n",
"# Icelandic ELECTRA-Base\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokeniz... |
null | transformers |
# Icelandic ELECTRA-Small
This model was pretrained on the [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/), which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.
# Acknowledgments
This research was supported with Cloud TPUs fr... | {"language": ["is"], "license": "cc-by-4.0", "datasets": ["igc"]} | jonfd/electra-small-igc-is | null | [
"transformers",
"pytorch",
"electra",
"pretraining",
"is",
"dataset:igc",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is"
] | TAGS
#transformers #pytorch #electra #pretraining #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us
|
# Icelandic ELECTRA-Small
This model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.
# Acknowledgments
This research was supported with Cloud TPUs from Google's TPU Research Cloud... | [
"# Icelandic ELECTRA-Small\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokenizer with a vocabulary size of 32,105.",
"# Acknowledgments\nThis research was supported with Cloud TPUs from Google's TPU Rese... | [
"TAGS\n#transformers #pytorch #electra #pretraining #is #dataset-igc #license-cc-by-4.0 #endpoints_compatible #region-us \n",
"# Icelandic ELECTRA-Small\nThis model was pretrained on the Icelandic Gigaword Corpus, which contains approximately 1.69B tokens, using default settings. The model uses a WordPiece tokeni... |
null | transformers |
# Icelandic-Norwegian ELECTRA-Small
This model was pretrained on the following corpora:
* The [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/) (IGC)
* The Icelandic Common Crawl Corpus (IC3)
* The [Icelandic Crawled Corpus](https://huggingface.co/datasets/jonfd/ICC) (ICC)
* The [Multilingual Colossal Clean Craw... | {"language": ["is", false], "license": "cc-by-4.0", "datasets": ["igc", "ic3", "jonfd/ICC", "mc4"]} | jonfd/electra-small-is-no | null | [
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"dataset:igc",
"dataset:ic3",
"dataset:jonfd/ICC",
"dataset:mc4",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is",
"no"
] | TAGS
#transformers #pytorch #tf #electra #pretraining #is #no #dataset-igc #dataset-ic3 #dataset-jonfd/ICC #dataset-mc4 #license-cc-by-4.0 #endpoints_compatible #region-us
|
# Icelandic-Norwegian ELECTRA-Small
This model was pretrained on the following corpora:
* The Icelandic Gigaword Corpus (IGC)
* The Icelandic Common Crawl Corpus (IC3)
* The Icelandic Crawled Corpus (ICC)
* The Multilingual Colossal Clean Crawled Corpus (mC4) - Icelandic and Norwegian text obtained from .is and .no do... | [
"# Icelandic-Norwegian ELECTRA-Small\nThis model was pretrained on the following corpora:\n* The Icelandic Gigaword Corpus (IGC)\n* The Icelandic Common Crawl Corpus (IC3)\n* The Icelandic Crawled Corpus (ICC)\n* The Multilingual Colossal Clean Crawled Corpus (mC4) - Icelandic and Norwegian text obtained from .is a... | [
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"# Icelandic-Norwegian ELECTRA-Small\nThis model was pretrained on the following corpora:\n* The Icelandic Gigaword Corpus (IGC)\n* The... |
null | transformers |
# Nordic ELECTRA-Small
This model was pretrained on the following corpora:
* The [Icelandic Gigaword Corpus](http://igc.arnastofnun.is/) (IGC)
* The Icelandic Common Crawl Corpus (IC3)
* The [Icelandic Crawled Corpus](https://huggingface.co/datasets/jonfd/ICC) (ICC)
* The [Multilingual Colossal Clean Crawled Corpus](h... | {"language": ["is", false, "sv", "da"], "license": "cc-by-4.0", "datasets": ["igc", "ic3", "jonfd/ICC", "mc4"]} | jonfd/electra-small-nordic | null | [
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"dataset:jonfd/ICC",
"dataset:mc4",
"license:cc-by-4.0",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"is",
"no",
"sv",
"da"
] | TAGS
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|
# Nordic ELECTRA-Small
This model was pretrained on the following corpora:
* The Icelandic Gigaword Corpus (IGC)
* The Icelandic Common Crawl Corpus (IC3)
* The Icelandic Crawled Corpus (ICC)
* The Multilingual Colossal Clean Crawled Corpus (mC4) - Icelandic, Norwegian, Swedish and Danish text obtained from .is, .no, ... | [
"# Nordic ELECTRA-Small\nThis model was pretrained on the following corpora:\n* The Icelandic Gigaword Corpus (IGC)\n* The Icelandic Common Crawl Corpus (IC3)\n* The Icelandic Crawled Corpus (ICC)\n* The Multilingual Colossal Clean Crawled Corpus (mC4) - Icelandic, Norwegian, Swedish and Danish text obtained from .... | [
"TAGS\n#transformers #pytorch #tf #electra #pretraining #is #no #sv #da #dataset-igc #dataset-ic3 #dataset-jonfd/ICC #dataset-mc4 #license-cc-by-4.0 #endpoints_compatible #has_space #region-us \n",
"# Nordic ELECTRA-Small\nThis model was pretrained on the following corpora:\n* The Icelandic Gigaword Corpus (IGC)\... |
text-classification | transformers | ---
Epoch Training Loss Validation Loss F1 Roc Auc Accuracy
1 0.115400 0.099458 0.888763 0.920410 0.731760
2 0.070400 0.080343 0.911700 0.943234 0.781116 | {} | joniponi/bert-finetuned-sem_eval-english | 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
| ---
Epoch Training Loss Validation Loss F1 Roc Auc Accuracy
1 0.115400 0.099458 0.888763 0.920410 0.731760
2 0.070400 0.080343 0.911700 0.943234 0.781116 | [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
null | null | The following model is trained on the SUM partition of 20% overlapping mixtures | {} | jonpodtu/02sparseOverlapConvTasNet_SUM_2spk_8k | null | [
"pytorch",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#pytorch #region-us
| The following model is trained on the SUM partition of 20% overlapping mixtures | [] | [
"TAGS\n#pytorch #region-us \n"
] |
text-generation | transformers | # Summary
The app was conceived with the idea of recreating and generate new dialogs for existing games.
In order to generate a dataset for training the steps followed were:
1. Download from [Assassins Creed Fandom Wiki](https://assassinscreed.fandom.com/wiki/Special:Export) from the category "Memories relived using th... | {} | jonx18/DialoGPT-small-Creed-Odyssey | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| # Summary
The app was conceived with the idea of recreating and generate new dialogs for existing games.
In order to generate a dataset for training the steps followed were:
1. Download from Assassins Creed Fandom Wiki from the category "Memories relived using the Animus HR-8.5".
2. Keep only text elements from XML.
3.... | [
"# Summary\nThe app was conceived with the idea of recreating and generate new dialogs for existing games.\nIn order to generate a dataset for training the steps followed were:\n1. Download from Assassins Creed Fandom Wiki from the category \"Memories relived using the Animus HR-8.5\".\n2. Keep only text elements f... | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Summary\nThe app was conceived with the idea of recreating and generate new dialogs for existing games.\nIn order to generate a dataset for training the steps followe... |
token-classification | transformers | * Fine-tunning "KLUE/roberta-large" model For CER(Company Entity Recognition) With Custom Dataset
* Custom Datasets are composed of news data
```python
label_list = ['O',"B-PER","I-PER","B-ORG","I-ORG","B-COM","I-COM","B-LOC","I-LOC","B-DAT","I-DAT","B-TIM","I-TIM","B-QNT","I-QNT"]
refer_list = ['0','1','2','3','4... | {} | joonhan/roberta-roa | null | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #token-classification #autotrain_compatible #endpoints_compatible #region-us
| * Fine-tunning "KLUE/roberta-large" model For CER(Company Entity Recognition) With Custom Dataset
* Custom Datasets are composed of news data
- EX: "B-PER" : 1 , "B-COM" : 5 | [] | [
"TAGS\n#transformers #pytorch #roberta #token-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Portuguese using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language model) as follows:
```p... | {"language": "pt", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "pt", "apache-2.0", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week", "PyTorch"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga XLSR Wav2Vec2 Large... | joaoalvarenga/model-sid-voxforge-cv-cetuc-0 | null | [
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"wav2vec2",
"automatic-speech-recognition",
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"portuguese-speech-corpus",
"xlsr-fine-tuning-week",
"PyTorch",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Portuguese test data of Common Voice.
Test ... | [
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Portuguese test data of Common Vo... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebo... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Portuguese using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language model) as follows:
```p... | {"language": "pt", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "pt", "apache-2.0", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week", "PyTorch"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga XLSR Wav2Vec2 Large... | joaoalvarenga/wav2vec2-cv-coral-30ep | null | [
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"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
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"apache-2.0",
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"xlsr-fine-tuning-week",
"PyTorch",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Portuguese test data of Common Voice.
Test ... | [
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Portuguese test data of Common Vo... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebo... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-100k-VoxPopuli-Portuguese
Fine-tuned [facebook/wav2vec2-large-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-large-100k-voxpopuli) on Portuguese using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language mod... | {"language": "pt", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "pt", "apache-2.0", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "PyTorch", "voxpopuli"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga Wav2Vec2 Large 100k VoxPopuli P... | joaoalvarenga/wav2vec2-large-100k-voxpopuli-pt | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"pt",
"apache-2.0",
"portuguese-speech-corpus",
"PyTorch",
"voxpopuli",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #PyTorch #voxpopuli #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-100k-VoxPopuli-Portuguese
Fine-tuned facebook/wav2vec2-large-100k-voxpopuli on Portuguese using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Portuguese test data of Common Vo... | [
"# Wav2Vec2-Large-100k-VoxPopuli-Portuguese\n\nFine-tuned facebook/wav2vec2-large-100k-voxpopuli on Portuguese using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Portuguese test dat... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #PyTorch #voxpopuli #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-100k-VoxPopuli-Portuguese\n\nFine-tuned facebook/wa... |
automatic-speech-recognition | null |
# Wav2Vec2-Large-XLSR-53-Spanish
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Spanish using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language model) as follows:
```python
... | {"language": "es", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "es", "apache-2.0", "spanish-speech-corpus", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week", "PyTorch"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga XLSR Wav2Vec2 Large 53... | joaoalvarenga/wav2vec2-large-xlsr-53-spanish | null | [
"audio",
"speech",
"wav2vec2",
"es",
"apache-2.0",
"spanish-speech-corpus",
"automatic-speech-recognition",
"xlsr-fine-tuning-week",
"PyTorch",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#audio #speech #wav2vec2 #es #apache-2.0 #spanish-speech-corpus #automatic-speech-recognition #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #region-us
|
# Wav2Vec2-Large-XLSR-53-Spanish
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Spanish using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Portuguese test data of Common Voice.
Test Result... | [
"# Wav2Vec2-Large-XLSR-53-Spanish\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Spanish using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Portuguese test data of Common Voice.\n... | [
"TAGS\n#audio #speech #wav2vec2 #es #apache-2.0 #spanish-speech-corpus #automatic-speech-recognition #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Spanish\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Spanish using the Common Vo... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Italian
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Italian using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language model) as follows:
```python
... | {"language": "it", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "it", "apache-2.0", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week", "PyTorch"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga XLSR Wav2Vec2 Large... | joaoalvarenga/wav2vec2-large-xlsr-italian | null | [
"transformers",
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"it",
"apache-2.0",
"portuguese-speech-corpus",
"xlsr-fine-tuning-week",
"PyTorch",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"it"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #it #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Italian
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Italian using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Italian test data of Common Voice.
Test Result (w... | [
"# Wav2Vec2-Large-XLSR-53-Italian\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Italian using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Italian test data of Common Voice.\n\n\... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #it #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Italian\n\nFine-tuned facebook/... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Portuguese using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language model) as follows:
```p... | {"language": "pt", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "pt", "apache-2.0", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week", "PyTorch"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga XLSR Wav2Vec2 Large... | joaoalvarenga/wav2vec2-large-xlsr-portuguese-a | null | [
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"PyTorch",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Portuguese test data of Common Voice.
Test ... | [
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Portuguese test data of Common Vo... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebo... |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Portuguese using the [Common Voice](https://huggingface.co/datasets/common_voice) dataset.
## Usage
The model can be used directly (without a language model) as follows:
```p... | {"language": "pt", "license": "apache-2.0", "tags": ["audio", "speech", "wav2vec2", "pt", "apache-2.0", "portuguese-speech-corpus", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week", "PyTorch"], "datasets": ["common_voice"], "metrics": ["wer"], "model-index": [{"name": "JoaoAlvarenga XLSR Wav2Vec2 Large... | joaoalvarenga/wav2vec2-large-xlsr-portuguese | null | [
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"wav2vec2",
"automatic-speech-recognition",
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"xlsr-fine-tuning-week",
"PyTorch",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"pt"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-Portuguese
Fine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the Portuguese test data of Common Voice.
You need... | [
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 on Portuguese using the Common Voice dataset.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be evaluated as follows on the Portuguese test data of Common Vo... | [
"TAGS\n#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #pt #apache-2.0 #portuguese-speech-corpus #xlsr-fine-tuning-week #PyTorch #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-Portuguese\n\nFine-tuned facebo... |
text-generation | transformers |
### About NegaNetizen
Trained on conversations from a friend for use within their discord server.
### How to use
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained('j... | {"language": ["en"], "tags": ["conversational", "gpt2"], "datasets": ["Discord transcripts"]} | jordanhagan/DialoGPT-medium-NegaNetizen | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
### About NegaNetizen
Trained on conversations from a friend for use within their discord server.
### How to use
| [
"### About NegaNetizen\nTrained on conversations from a friend for use within their discord server.",
"### How to use"
] | [
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"### About NegaNetizen\nTrained on conversations from a friend for use within their discord server.",
"### How to use"
] |
null | opennmt |
### Introduction
This repository contains a description on how to use OpenNMT on the Grammar Error Correction (GEC) task. The idea is to approch GEC as a translation task
### Usage
Install the necessary dependencies:
```bash
pip3 install ctranslate2 pyonmttok
```
Simple tokenization & translation using Python:
... | {"language": ["en"], "license": "mit", "library_name": "opennmt", "tags": ["gec"], "metrics": ["bleu"], "inference": false} | jordimas/gec-opennmt-english | null | [
"opennmt",
"gec",
"en",
"arxiv:2106.03830",
"license:mit",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2106.03830"
] | [
"en"
] | TAGS
#opennmt #gec #en #arxiv-2106.03830 #license-mit #region-us
|
### Introduction
This repository contains a description on how to use OpenNMT on the Grammar Error Correction (GEC) task. The idea is to approch GEC as a translation task
### Usage
Install the necessary dependencies:
Simple tokenization & translation using Python:
# Model
The model has been training using... | [
"### Introduction\n\nThis repository contains a description on how to use OpenNMT on the Grammar Error Correction (GEC) task. The idea is to approch GEC as a translation task",
"### Usage\n\nInstall the necessary dependencies:\n\n\n\n\n\nSimple tokenization & translation using Python:",
"# Model\n\nThe model ha... | [
"TAGS\n#opennmt #gec #en #arxiv-2106.03830 #license-mit #region-us \n",
"### Introduction\n\nThis repository contains a description on how to use OpenNMT on the Grammar Error Correction (GEC) task. The idea is to approch GEC as a translation task",
"### Usage\n\nInstall the necessary dependencies:\n\n\n\n\n\nSi... |
null | null | test | {} | jordn/thing | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| test | [] | [
"TAGS\n#region-us \n"
] |
text-classification | transformers | This model is a bert for sequence classification model fine-tuned on the MedDialogue dataset. Basically, the task is just to predict if a given sentence in the corpus was spoken by the patient or doctor. | {} | josephgatto/paint_doctor_speaker_identification | 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
| This model is a bert for sequence classification model fine-tuned on the MedDialogue dataset. Basically, the task is just to predict if a given sentence in the corpus was spoken by the patient or doctor. | [] | [
"TAGS\n#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
# Alfred DialoGPT | {"tags": ["conversational"]} | josephmagnayon/DialoGPT-medium-Alfred | 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
|
# Alfred DialoGPT | [
"# Alfred DialoGPT"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Alfred DialoGPT"
] |
text-generation | transformers |
# HumanChat Model | {"tags": ["conversational"]} | josepjulia/RepoHumanChatBot | 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
|
# HumanChat Model | [
"# HumanChat Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# HumanChat Model"
] |
text-generation | transformers |
# Josh DialoGPT medium Bot | {"tags": ["conversational"]} | josh8/DialoGPT-medium-josh | 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
|
# Josh DialoGPT medium Bot | [
"# Josh DialoGPT medium Bot"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Josh DialoGPT medium Bot"
] |
text-generation | transformers |
# Josh DialoGPT Model | {"tags": ["conversational"]} | josh8/DialoGPT-small-josh | 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
|
# Josh DialoGPT Model | [
"# Josh DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Josh DialoGPT Model"
] |
summarization | transformers | # mt5-small-spanish-summarization
## Model description
This is a mt5-small model finetuned for generating headlines from the body of the news in Spanish.
## Training data
The model was trained with 58425 news extracted from the La Razón (31477) and Público (26948) newspapers. These news belong to the following cat... | {"language": ["es"], "license": "apache-2.0", "tags": ["summarization", "mt5", "spanish"], "datasets": ["larazonpublico", "es"], "metrics": ["rouge"], "widget": [{"text": "La Guardia Civil ha desarticulado un grupo organizado dedicado a copiar en los examenes teoricos para la obtencion del permiso de conducir. Para ell... | josmunpen/mt5-small-spanish-summarization | null | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"summarization",
"spanish",
"es",
"dataset:larazonpublico",
"dataset:es",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #mt5 #text2text-generation #summarization #spanish #es #dataset-larazonpublico #dataset-es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| mt5-small-spanish-summarization
===============================
Model description
-----------------
This is a mt5-small model finetuned for generating headlines from the body of the news in Spanish.
Training data
-------------
The model was trained with 58425 news extracted from the La Razón (31477) and Público... | [
"### Hyperparameters\n\n\n{evaluation\\_strategy = \"epoch\",\nlearning\\_rate = 2e-4,\nper\\_device\\_train\\_batch\\_size = 6,\nper\\_device\\_eval\\_batch\\_size = 6,\nweight\\_decay = 0.01,\nsave\\_total\\_limi t= 3,\nnum\\_train\\_epochs = 2,\npredict\\_with\\_generate = True,\nfp16 = False}\n\n\nEval results\... | [
"TAGS\n#transformers #pytorch #mt5 #text2text-generation #summarization #spanish #es #dataset-larazonpublico #dataset-es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Hyperparameters\n\n\n{evaluation\\_strategy = \"epoch\",\nlearning\\_rate = 2e-4,... |
multiple-choice | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-uncased-finetuned-swag
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-unca... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-base-uncased-finetuned-swag", "results": []}]} | joykirat/bert-base-uncased-finetuned-swag | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"multiple-choice",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
|
# bert-base-uncased-finetuned-swag
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyp... | [
"# bert-base-uncased-finetuned-swag\n\nThis model is a fine-tuned version of bert-base-uncased on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training p... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"# bert-base-uncased-finetuned-swag\n\nThis model is a fine-tuned version of bert-base-uncased on an unknown dataset.",
"## Model description\n\nMore information ne... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model-index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "ar... | jpabbuehl/distilbert-base-uncased-finetuned-cola | null | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"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 #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| distilbert-base-uncased-finetuned-cola
======================================
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset.
It achieves the following results on the evaluation set:
* Loss: 0.7588
* Matthews Correlation: 0.5230
Model description
-----------------
More informa... | [
"### 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",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-glue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sagemaker-distilbert-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-b... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "metrics": ["accuracy"], "model-index": [{"name": "sagemaker-distilbert-emotion", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "emotion", "type": "emotion", "args": "default... | jpabbuehl/sagemaker-distilbert-emotion | null | [
"transformers",
"pytorch",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| sagemaker-distilbert-emotion
============================
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1446
* Accuracy: 0.929
Model description
-----------------
More information needed
Intended uses & ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 64\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 #distilbert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3... |
summarization | transformers |
# Samsum Pegasus (Reddit/TIFU) for conversational summaries
## Model description
Pegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!
## Training data
The data is the [samsum](https://huggingface.co/datasets/samsum) dataset for conversional summaries.
The initial weigths were from the... | {"language": ["en"], "tags": ["pytorch", "google/pegasus-reddit_tifu", "summarization", "samsum"], "datasets": ["samsum"], "metrics": ["rouge"]} | jpcorb20/pegasus-large-reddit_tifu-samsum-256 | null | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"google/pegasus-reddit_tifu",
"summarization",
"samsum",
"en",
"dataset:samsum",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #pegasus #text2text-generation #google/pegasus-reddit_tifu #summarization #samsum #en #dataset-samsum #autotrain_compatible #endpoints_compatible #region-us
|
# Samsum Pegasus (Reddit/TIFU) for conversational summaries
## Model description
Pegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!
## Training data
The data is the samsum dataset for conversional summaries.
The initial weigths were from the google/pegasus-reddit_tifu. The hypothesi... | [
"# Samsum Pegasus (Reddit/TIFU) for conversational summaries",
"## Model description\n\nPegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!",
"## Training data\n\nThe data is the samsum dataset for conversional summaries.\n\nThe initial weigths were from the google/pegasus-reddit_t... | [
"TAGS\n#transformers #pytorch #pegasus #text2text-generation #google/pegasus-reddit_tifu #summarization #samsum #en #dataset-samsum #autotrain_compatible #endpoints_compatible #region-us \n",
"# Samsum Pegasus (Reddit/TIFU) for conversational summaries",
"## Model description\n\nPegasus (Reddit/TIFU) for conver... |
summarization | transformers |
# Samsum Pegasus (Reddit/TIFU) for conversational summaries
## Model description
Pegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!
## Training data
The data is the [samsum](https://huggingface.co/datasets/samsum) dataset for conversional summaries.
The initial weigths were from the... | {"language": ["en"], "tags": ["pytorch", "google/pegasus-reddit_tifu", "summarization", "samsum"], "datasets": ["samsum"], "metrics": ["rouge"]} | jpcorb20/pegasus-large-reddit_tifu-samsum-512 | null | [
"transformers",
"pytorch",
"pegasus",
"text2text-generation",
"google/pegasus-reddit_tifu",
"summarization",
"samsum",
"en",
"dataset:samsum",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #pegasus #text2text-generation #google/pegasus-reddit_tifu #summarization #samsum #en #dataset-samsum #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# Samsum Pegasus (Reddit/TIFU) for conversational summaries
## Model description
Pegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!
## Training data
The data is the samsum dataset for conversional summaries.
The initial weigths were from the google/pegasus-reddit_tifu. The hypothesi... | [
"# Samsum Pegasus (Reddit/TIFU) for conversational summaries",
"## Model description\n\nPegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!",
"## Training data\n\nThe data is the samsum dataset for conversional summaries.\n\nThe initial weigths were from the google/pegasus-reddit_t... | [
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"# Samsum Pegasus (Reddit/TIFU) for conversational summaries",
"## Model description\n\nPegasus (Reddit/TIFU)... |
text-classification | transformers | # Distilroberta for toxic comment detection
See my GitHub repo [toxic-comment-server](https://github.com/jpcorb20/toxic-comment-server)
The model was trained from [DistilRoberta](https://huggingface.co/distilroberta-base) on [Kaggle Toxic Comments](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challeng... | {} | jpcorb20/toxic-detector-distilroberta | null | [
"transformers",
"pytorch",
"jax",
"roberta",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us
| # Distilroberta for toxic comment detection
See my GitHub repo toxic-comment-server
The model was trained from DistilRoberta on Kaggle Toxic Comments with the BCEWithLogits loss for Multi-Label prediction. Thus, please use the sigmoid activation on the logits (not made to use the softmax output, e.g. like the HF widg... | [
"# Distilroberta for toxic comment detection\n\nSee my GitHub repo toxic-comment-server\n\nThe model was trained from DistilRoberta on Kaggle Toxic Comments with the BCEWithLogits loss for Multi-Label prediction. Thus, please use the sigmoid activation on the logits (not made to use the softmax output, e.g. like th... | [
"TAGS\n#transformers #pytorch #jax #roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us \n",
"# Distilroberta for toxic comment detection\n\nSee my GitHub repo toxic-comment-server\n\nThe model was trained from DistilRoberta on Kaggle Toxic Comments with the BCEWithLogits loss for ... |
text-classification | transformers |
# Longformer-base for Machine-Paraphrase Detection
If you are using this model in your research work, please cite
```
@InProceedings{10.1007/978-3-030-96957-8_34,
author="Wahle, Jan Philip and Ruas, Terry and Folt{\'y}nek, Tom{\'a}{\v{s}} and Meuschke, Norman and Gipp, Bela",
title="Identifying Machine-Parap... | {"language": "en", "tags": ["array", "of", "tags"], "datasets": ["jpwahle/machine-paraphrase-dataset"], "thumbnail": "url to a thumbnail used in social sharing", "widget": [{"text": "Plagiarism is the representation of another author's writing, thoughts, ideas, or expressions as one's own work."}]} | jpwahle/longformer-base-plagiarism-detection | null | [
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"safetensors",
"longformer",
"text-classification",
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"dataset:jpwahle/machine-paraphrase-dataset",
"arxiv:2004.05150",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2004.05150"
] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #longformer #text-classification #array #of #tags #en #dataset-jpwahle/machine-paraphrase-dataset #arxiv-2004.05150 #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# Longformer-base for Machine-Paraphrase Detection
If you are using this model in your research work, please cite
This is the checkpoint for Longformer-base after being trained on the Machine-Paraphrased Plagiarism Dataset
Additional information about this model:
* The longformer-base-4096 model page
* Longforme... | [
"# Longformer-base for Machine-Paraphrase Detection\n\nIf you are using this model in your research work, please cite\n\n\n\nThis is the checkpoint for Longformer-base after being trained on the Machine-Paraphrased Plagiarism Dataset\n\nAdditional information about this model:\n\n* The longformer-base-4096 model pa... | [
"TAGS\n#transformers #pytorch #safetensors #longformer #text-classification #array #of #tags #en #dataset-jpwahle/machine-paraphrase-dataset #arxiv-2004.05150 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# Longformer-base for Machine-Paraphrase Detection\n\nIf you are using this model i... |
text2text-generation | transformers |
# T5-large for Word Sense Disambiguation
If you are using this model in your research work, please cite
```bib
@article{wahle2021incorporating,
title={Incorporating Word Sense Disambiguation in Neural Language Models},
author={Wahle, Jan Philip and Ruas, Terry and Meuschke, Norman and Gipp, Bela},
journal={arX... | {"language": "en", "tags": ["array", "of", "tags"], "thumbnail": "url to a thumbnail used in social sharing", "widget": [{"text": "question: which description describes the word \" java \" best in the following context? descriptions: [ \" A drink consisting of an infusion of ground coffee beans \" , \" a platform-ind... | jpwahle/t5-large-word-sense-disambiguation | null | [
"transformers",
"pytorch",
"safetensors",
"t5",
"text2text-generation",
"array",
"of",
"tags",
"en",
"arxiv:1910.10683",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1910.10683"
] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #array #of #tags #en #arxiv-1910.10683 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
|
# T5-large for Word Sense Disambiguation
If you are using this model in your research work, please cite
This is the checkpoint for T5-large after being trained on the SemCor 3.0 dataset.
Additional information about this model:
* The t5-large model page
* Exploring the Limits of Transfer Learning with a Unified ... | [
"# T5-large for Word Sense Disambiguation\n\nIf you are using this model in your research work, please cite\n\n\n\nThis is the checkpoint for T5-large after being trained on the SemCor 3.0 dataset.\n\nAdditional information about this model:\n\n* The t5-large model page\n* Exploring the Limits of Transfer Learning ... | [
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"# T5-large for Word Sense Disambiguation\n\nIf you are using this model in your research work, please cite\... |
fill-mask | transformers | # Tensorflow CamemBERT
In this repository you will find different versions of the CamemBERT model for Tensorflow.
## CamemBERT
[CamemBERT](https://camembert-model.fr/) is a state-of-the-art language model for French based on the RoBERTa architecture pretrained on the French subcorpus of the newly available multiling... | {} | jplu/tf-camembert-base | null | [
"transformers",
"tf",
"camembert",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #tf #camembert #fill-mask #autotrain_compatible #endpoints_compatible #region-us
| Tensorflow CamemBERT
====================
In this repository you will find different versions of the CamemBERT model for Tensorflow.
CamemBERT
---------
CamemBERT is a state-of-the-art language model for French based on the RoBERTa architecture pretrained on the French subcorpus of the newly available multilingua... | [] | [
"TAGS\n#transformers #tf #camembert #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n"
] |
token-classification | transformers |
# XLM-R + NER
This model is a fine-tuned [XLM-Roberta-base](https://arxiv.org/abs/1911.02116) over the 40 languages proposed in [XTREME](https://github.com/google-research/xtreme) from [Wikiann](https://aclweb.org/anthology/P17-1178). This is still an on-going work and the results will be updated everytime an improv... | {"language": ["multilingual", "af", "ar", "bg", "bn", "de", "el", "en", "es", "et", "eu", "fa", "fi", "fr", "he", "hi", "hu", "id", "it", "ja", "jv", "ka", "kk", "ko", "ml", "mr", "ms", "my", "nl", "pt", "ru", "sw", "ta", "te", "th", "tl", "tr", "ur", "vi", "yo", "zh"], "language_bcp47": ["fa-IR"]} | jplu/tf-xlm-r-ner-40-lang | null | [
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"multilingual",
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"my",
"nl",
"pt",... | null | 2022-03-02T23:29:05+00:00 | [
"1911.02116"
] | [
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"nl",
"pt",
"ru",
"sw",
"ta",
"te",
"th",
"tl",
"tr",
"ur",
"v... | TAGS
#transformers #tf #xlm-roberta #token-classification #multilingual #af #ar #bg #bn #de #el #en #es #et #eu #fa #fi #fr #he #hi #hu #id #it #ja #jv #ka #kk #ko #ml #mr #ms #my #nl #pt #ru #sw #ta #te #th #tl #tr #ur #vi #yo #zh #arxiv-1911.02116 #autotrain_compatible #endpoints_compatible #region-us
|
# XLM-R + NER
This model is a fine-tuned XLM-Roberta-base over the 40 languages proposed in XTREME from Wikiann. This is still an on-going work and the results will be updated everytime an improvement is reached.
The covered labels are:
## Metrics on evaluation set:
### Average over the 40 languages
Number of do... | [
"# XLM-R + NER\n\nThis model is a fine-tuned XLM-Roberta-base over the 40 languages proposed in XTREME from Wikiann. This is still an on-going work and the results will be updated everytime an improvement is reached. \n\nThe covered labels are:",
"## Metrics on evaluation set:",
"### Average over the 40 langua... | [
"TAGS\n#transformers #tf #xlm-roberta #token-classification #multilingual #af #ar #bg #bn #de #el #en #es #et #eu #fa #fi #fr #he #hi #hu #id #it #ja #jv #ka #kk #ko #ml #mr #ms #my #nl #pt #ru #sw #ta #te #th #tl #tr #ur #vi #yo #zh #arxiv-1911.02116 #autotrain_compatible #endpoints_compatible #region-us \n",
"#... |
fill-mask | transformers | # Tensorflow XLM-RoBERTa
In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
## XLM-RoBERTa
[XLM-RoBERTa](https://ai.facebook.com/blog/-xlm-r-state-of-the-art-cross-lingual-understanding-through-self-supervision/) is a scaled cross lingual sentence encoder. It is trained on 2... | {} | jplu/tf-xlm-roberta-base | null | [
"transformers",
"tf",
"xlm-roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #tf #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us
| Tensorflow XLM-RoBERTa
======================
In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
XLM-RoBERTa
-----------
XLM-RoBERTa is a scaled cross lingual sentence encoder. It is trained on 2.5T of data across 100 languages data filtered from Common Crawl. XLM-R achie... | [] | [
"TAGS\n#transformers #tf #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n"
] |
fill-mask | transformers | # Tensorflow XLM-RoBERTa
In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
## XLM-RoBERTa
[XLM-RoBERTa](https://ai.facebook.com/blog/-xlm-r-state-of-the-art-cross-lingual-understanding-through-self-supervision/) is a scaled cross lingual sentence encoder. It is trained on 2... | {} | jplu/tf-xlm-roberta-large | null | [
"transformers",
"tf",
"xlm-roberta",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #tf #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us
| Tensorflow XLM-RoBERTa
======================
In this repository you will find different versions of the XLM-RoBERTa model for Tensorflow.
XLM-RoBERTa
-----------
XLM-RoBERTa is a scaled cross lingual sentence encoder. It is trained on 2.5T of data across 100 languages data filtered from Common Crawl. XLM-R achie... | [] | [
"TAGS\n#transformers #tf #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers | First model for storytelling
| {} | jppaolim/homerGPT2 | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| First model for storytelling
| [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers | Second model for storytelling
| {} | jppaolim/homerGPT2L | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Second model for storytelling
| [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
# Harry Potter DialoGPT Model | {"tags": ["conversational"]} | jpsxlr8/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 | [
"# Harry Potter DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Harry Potter DialoGPT Model"
] |
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. -->
# urdu-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-3... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "urdu-colab", "results": []}]} | js-rockstar/urdu-colab | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
|
# urdu-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
... | [
"# urdu-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us \n",
"# urdu-colab\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.",
"## Model description\n\nMore information needed",
... |
text2text-generation | transformers |
Answer generator model of [ELI5-Category Dataset](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/) | {"language": "en", "license": "mit", "datasets": ["eli5_category"]} | jsgao/bart-eli5c | null | [
"transformers",
"pytorch",
"safetensors",
"bart",
"text2text-generation",
"en",
"dataset:eli5_category",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #bart #text2text-generation #en #dataset-eli5_category #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
Answer generator model of ELI5-Category Dataset | [] | [
"TAGS\n#transformers #pytorch #safetensors #bart #text2text-generation #en #dataset-eli5_category #license-mit #autotrain_compatible #endpoints_compatible #region-us \n"
] |
feature-extraction | transformers |
Document Retriever model of [ELI5-Category Dataset](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/), need additional projection layer (see GitHub [repo](https://github.com/rexarski/ANLY580-final-project/blob/main/model_deploy/models/eli5c_qa_model.py)) | {"language": "en", "license": "MIT", "datasets": ["eli5_category"]} | jsgao/bert-eli5c-retriever | null | [
"transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"en",
"dataset:eli5_category",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #bert #feature-extraction #en #dataset-eli5_category #endpoints_compatible #region-us
|
Document Retriever model of ELI5-Category Dataset, need additional projection layer (see GitHub repo) | [] | [
"TAGS\n#transformers #pytorch #safetensors #bert #feature-extraction #en #dataset-eli5_category #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-German-GPT2
This is an encoder-decoder model for automatic speech recognition trained on on the
MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - DE dataset. The encoder was initialized from
[jonatasgrosman/wav2vec2-large-xlsr-53-german](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-german... | {"language": ["de"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "de", "hf-asr-leaderboard", "mozilla-foundation/common_voice_7_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_7_0"], "model-index": [{"name": "Wav2Vec2-Large-XLSR-53-German-GPT2", "results": [{"task": {"typ... | jsnfly/wav2vec2-large-xlsr-53-german-gpt2 | null | [
"transformers",
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"de",
"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:u... | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #speech-encoder-decoder #automatic-speech-recognition #de #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-XLSR-53-German-GPT2
This is an encoder-decoder model for automatic speech recognition trained on on the
MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - DE dataset. The encoder was initialized from
jonatasgrosman/wav2vec2-large-xlsr-53-german and
the decoder from dbmdz/german-gpt2.
It was trained using a two s... | [
"# Wav2Vec2-Large-XLSR-53-German-GPT2\n\nThis is an encoder-decoder model for automatic speech recognition trained on on the\nMOZILLA-FOUNDATION/COMMON_VOICE_7_0 - DE dataset. The encoder was initialized from\njonatasgrosman/wav2vec2-large-xlsr-53-german and\nthe decoder from dbmdz/german-gpt2.\n\nIt was trained us... | [
"TAGS\n#transformers #pytorch #speech-encoder-decoder #automatic-speech-recognition #de #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",
"# Wav2Vec2-Large-XLSR-53-German... |
automatic-speech-recognition | transformers |
# XLS-R-1b-DE
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - DE dataset. (See `run.sh` for training parameters). | {"language": ["de"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "de", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-1B - German", "results": [{"task": {"type": "automatic-sp... | jsnfly/wav2vec2-xls-r-1b-de-cv8 | null | [
"transformers",
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"hf-asr-leaderboard",
"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"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"de"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #de #hf-asr-leaderboard #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
|
# XLS-R-1b-DE
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - DE dataset. (See 'URL' for training parameters). | [
"# XLS-R-1b-DE\n\nThis model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - DE dataset. (See 'URL' for training parameters)."
] | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #de #hf-asr-leaderboard #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",
"# XLS-R-1b-DE\n\nThis model is a fine-tuned v... |
token-classification | transformers |
This is a SciBERT-based model fine-tuned to perform Named Entity Recognition for drug names and adverse drug effects.
This model classifies input tokens into one of five classes:
- `B-DRUG... | {"language": ["en"], "tags": ["Named Entity Recognition", "SciBERT", "Adverse Effect", "Drug", "Medical"], "datasets": ["ade_corpus_v2"], "widget": [{"text": "Abortion, miscarriage or uterine hemorrhage associated with misoprostol (Cytotec), a labor-inducing drug.", "example_title": "Abortion, miscarriage, ..."}, {"tex... | jsylee/scibert_scivocab_uncased-finetuned-ner | null | [
"transformers",
"pytorch",
"bert",
"token-classification",
"Named Entity Recognition",
"SciBERT",
"Adverse Effect",
"Drug",
"Medical",
"en",
"dataset:ade_corpus_v2",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bert #token-classification #Named Entity Recognition #SciBERT #Adverse Effect #Drug #Medical #en #dataset-ade_corpus_v2 #autotrain_compatible #endpoints_compatible #has_space #region-us
|
This is a SciBERT-based model fine-tuned to perform Named Entity Recognition for drug names and adverse drug effects.
!model image
This model classifies input tokens into one of five classes:
- 'B-DRUG': beginning of a drug entity
- 'I-DRUG': within a drug entity
- 'B-EFFECT': beginning of an AE entity
- 'I-EFFECT'... | [] | [
"TAGS\n#transformers #pytorch #bert #token-classification #Named Entity Recognition #SciBERT #Adverse Effect #Drug #Medical #en #dataset-ade_corpus_v2 #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
text-generation | transformers |
# Rick dialoGPT Model | {"tags": ["conversational"]} | jth1903/DialoGPT-small-rick | 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
|
# Rick dialoGPT Model | [
"# Rick dialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Rick dialoGPT Model"
] |
null | 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. -->
# outputs
This model is a fine-tuned version of [gerulata/slovakbert](https://huggingface.co/gerulata/slovakbert) on the [ju-bezde... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["ju-bezdek/conll2003-SK-NER"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "outputs", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "ju-bezdek/conll2003-SK-... | ju-bezdek/slovakbert-conll2003-sk-ner | null | [
"transformers",
"pytorch",
"generated_from_trainer",
"dataset:ju-bezdek/conll2003-SK-NER",
"license:mit",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #generated_from_trainer #dataset-ju-bezdek/conll2003-SK-NER #license-mit #model-index #endpoints_compatible #region-us
| outputs
=======
This model is a fine-tuned version of gerulata/slovakbert on the ju-bezdek/conll2003-SK-NER dataset.
It achieves the following results on the evaluation (validation) set:
* Loss: 0.1752
* Precision: 0.8190
* Recall: 0.8390
* F1: 0.8288
* Accuracy: 0.9526
Model description
-----------------
More ... | [
"### Result:\n\n\n\n\n\n Ruský\n MISC\n\n premiér \n \n Viktor Černomyrdin\n PER\n\n v piatok povedal, že prezident \n \n Boris Jeľcin,\n PER\n\n , ktorý je na dovolenke mimo \n \n Moskvy\n LOC\n\n , podporil mierový plán šéfa bezpečnosti \n \n Alexandra Lebedu\n PER\n\n pre \n \n Čečensko,\n LOC\n\n uviedla tlačov... | [
"TAGS\n#transformers #pytorch #generated_from_trainer #dataset-ju-bezdek/conll2003-SK-NER #license-mit #model-index #endpoints_compatible #region-us \n",
"### Result:\n\n\n\n\n\n Ruský\n MISC\n\n premiér \n \n Viktor Černomyrdin\n PER\n\n v piatok povedal, že prezident \n \n Boris Jeľcin,\n PER\n\n , ktorý je na ... |
image-classification | transformers |
# ice_cream
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpic... | {"tags": ["image-classification", "pytorch", "huggingpics"], "metrics": ["accuracy"]} | juanfiguera/ice_cream | null | [
"transformers",
"pytorch",
"tensorboard",
"vit",
"image-classification",
"huggingpics",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us
|
# ice_cream
Autogenerated by HuggingPics️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
## Example Images
#### chocolate ice cream
!chocolate ice cream
#### vanilla ice cream
!vanilla ice cream | [
"# ice_cream\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues with the demo at the github repo.",
"## Example Images",
"#### chocolate ice cream\n\n!chocolate ice cream",
"#### vanilla ice cream\n\n!vanilla ice cream"... | [
"TAGS\n#transformers #pytorch #tensorboard #vit #image-classification #huggingpics #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"# ice_cream\n\n\nAutogenerated by HuggingPics️\n\nCreate your own image classifier for anything by running the demo on Google Colab.\n\nReport any issues wit... |
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