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text2text-generation | transformers | # IT5 Base for Question Generation 💭 🇮🇹
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on question generation on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Text-to-text... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "question-generation", "squad_it", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Le conoscenze mediche erano stagnanti durante il Medioevo. Il resoconto pi\u00f9 autorev... | it5/it5-base-question-generation | null | [
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| # IT5 Base for Question Generation 🇮🇹
This repository contains the checkpoint for the IT5 Base model fine-tuned on question generation on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and Malv... | [
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text2text-generation | transformers | # IT5 Base for News Headline Style Transfer (Repubblica to Il Giornale) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part o... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/it5-base-repubblica-to-ilgiornale | null | [
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| # IT5 Base for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹
This repository contains the checkpoint for the IT5 Base model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-scale... | [
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... |
summarization | transformers | # IT5 Base for Wikipedia Summarization 📑 🇮🇹
This repository contains the checkpoint for the [IT5 Base](https://huggingface.co/gsarti/it5-base) model fine-tuned on Wikipedia summarization on the [WITS](https://www.semanticscholar.org/paper/WITS%3A-Wikipedia-for-Italian-Text-Summarization-Casola-Lavelli/ad6c83122e721... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "wikipedia", "summarization", "wits"], "datasets": ["wits"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "La 5\u00aa Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del p... | it5/it5-base-wiki-summarization | null | [
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| # IT5 Base for Wikipedia Summarization 🇮🇹
This repository contains the checkpoint for the IT5 Base model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and... | [
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text2text-generation | transformers |
# IT5 Large for Formal-to-informal Style Transfer 🤗
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Questa performance \u00e8 a dir poco spiacevole."}, {"text": "In attesa di un Suo cortese ris... | it5/it5-large-formal-to-informal | null | [
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# IT5 Large for Formal-to-informal Style Transfer
This repository contains the checkpoint for the IT5 Large model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Underst... | [
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text2text-generation | transformers | # IT5 Large for News Headline Generation 📣 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper [IT5: Large-scale Text-to-text Pretraining for Ita... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "headline-generation"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa deg... | it5/it5-large-headline-generation | null | [
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This repository contains the checkpoint for the IT5 Large model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by ... | [
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text2text-generation | transformers | # IT5 Large for News Headline Style Transfer (Il Giornale to Repubblica) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/it5-large-ilgiornale-to-repubblica | null | [
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| # IT5 Large for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹
This repository contains the checkpoint for the IT5 Large model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
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... |
text2text-generation | transformers |
# IT5 Base for Informal-to-formal Style Transfer 🧐
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to-... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "maronn qualcuno mi spieg' CHECCOSA SUCCEDE?!?!"}, {"text": "wellaaaaaaa, ma frat\u00e9 sei pr... | it5/it5-large-informal-to-formal | null | [
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|
# IT5 Base for Informal-to-formal Style Transfer
This repository contains the checkpoint for the IT5 Large model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understa... | [
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summarization | transformers | # IT5 Large for News Summarization ✂️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on news summarization on the [Fanpage](https://huggingface.co/datasets/ARTeLab/fanpage) and [Il Post](https://huggingface.co/datasets/ARTeLab/ilpost) corpo... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "fanpage", "ilpost", "summarization"], "datasets": ["ARTeLab/fanpage", "ARTeLab/ilpost"], "metrics": ["rouge"], "widget": [{"text": "Non lo vuole sposare. E\u2019 quanto emerge all\u2019interno dell\u2019ultima intervista di Raffa... | it5/it5-large-news-summarization | null | [
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| # IT5 Large for News Summarization ️️ 🇮🇹
This repository contains the checkpoint for the IT5 Large model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele ... | [
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text2text-generation | transformers | # IT5 Large for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on extractive question answering on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale ... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "squad_it", "text2text-question-answering", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["f1", "exact-match"], "widget": [{"text": "In seguito all' evento di estinzione del Cretaceo-Paleogene, l' estinzione dei d... | it5/it5-large-question-answering | null | [
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| # IT5 Large for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the IT5 Large model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele S... | [
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text2text-generation | transformers | # IT5 Large for Question Generation 💭 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on question generation on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Text-to-t... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "question-generation", "squad_it", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Le conoscenze mediche erano stagnanti durante il Medioevo. Il resoconto pi\u00f9 autorev... | it5/it5-large-question-generation | null | [
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| # IT5 Large for Question Generation 🇮🇹
This repository contains the checkpoint for the IT5 Large model fine-tuned on question generation on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and Ma... | [
"# IT5 Large for Question Generation 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Large model fine-tuned on question generation on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti... | [
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"# IT5 Large for Question G... |
text2text-generation | transformers | # IT5 Large for News Headline Style Transfer (Repubblica to Il Giornale) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/it5-large-repubblica-to-ilgiornale | null | [
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| # IT5 Large for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹
This repository contains the checkpoint for the IT5 Large model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
"# IT5 Large for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Large model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: La... | [
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... |
summarization | transformers | # IT5 Large for Wikipedia Summarization ✂️📑 🇮🇹
This repository contains the checkpoint for the [IT5 Large](https://huggingface.co/gsarti/it5-large) model fine-tuned on Wikipedia summarization on the [WITS](https://www.semanticscholar.org/paper/WITS%3A-Wikipedia-for-Italian-Text-Summarization-Casola-Lavelli/ad6c8312... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "wikipedia", "summarization", "wits"], "datasets": ["wits"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "La 5\u00aa Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del p... | it5/it5-large-wiki-summarization | null | [
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| # IT5 Large for Wikipedia Summarization ️ 🇮🇹
This repository contains the checkpoint for the IT5 Large model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti ... | [
"# IT5 Large for Wikipedia Summarization ️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Large model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele... | [
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"# IT5 Large for ... |
text2text-generation | transformers |
# IT5 Small for Formal-to-informal Style Transfer 🤗
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Questa performance \u00e8 a dir poco spiacevole."}, {"text": "In attesa di un Suo cortese ris... | it5/it5-small-formal-to-informal | null | [
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|
# IT5 Small for Formal-to-informal Style Transfer
This repository contains the checkpoint for the IT5 Small model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Underst... | [
"# IT5 Small for Formal-to-informal Style Transfer \n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language U... | [
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"# IT5 Small for Form... |
text2text-generation | transformers | # IT5 Small for News Headline Generation 📣 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper [IT5: Large-scale Text-to-text Pretraining for Ita... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "headline-generation"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa deg... | it5/it5-small-headline-generation | null | [
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| # IT5 Small for News Headline Generation 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by ... | [
"# IT5 Small for News Headline Generation 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generat... | [
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text2text-generation | transformers | # IT5 Small for News Headline Style Transfer (Il Giornale to Repubblica) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/it5-small-ilgiornale-to-repubblica | null | [
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| # IT5 Small for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
"# IT5 Small for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: La... | [
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... |
text2text-generation | transformers |
# IT5 Small for Informal-to-formal Style Transfer 🧐
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "maronn qualcuno mi spieg' CHECCOSA SUCCEDE?!?!"}, {"text": "wellaaaaaaa, ma frat\u00e9 sei pr... | it5/it5-small-informal-to-formal | null | [
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|
# IT5 Small for Informal-to-formal Style Transfer
This repository contains the checkpoint for the IT5 Small model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Underst... | [
"# IT5 Small for Informal-to-formal Style Transfer \n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language U... | [
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"# IT5 Small for Info... |
summarization | transformers | # IT5 Small for News Summarization ✂️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on news summarization on the [Fanpage](https://huggingface.co/datasets/ARTeLab/fanpage) and [Il Post](https://huggingface.co/datasets/ARTeLab/ilpost) corpo... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "fanpage", "ilpost", "summarization"], "datasets": ["ARTeLab/fanpage", "ARTeLab/ilpost"], "metrics": ["rouge"], "widget": [{"text": "Non lo vuole sposare. E\u2019 quanto emerge all\u2019interno dell\u2019ultima intervista di Raffa... | it5/it5-small-news-summarization | null | [
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| # IT5 Small for News Summarization ️️ 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele ... | [
"# IT5 Small for News Summarization ️️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Ga... | [
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text2text-generation | transformers | # IT5 Small for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on extractive question answering on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale ... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "squad_it", "text2text-question-answering", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["f1", "exact-match"], "widget": [{"text": "In seguito all' evento di estinzione del Cretaceo-Paleogene, l' estinzione dei d... | it5/it5-small-question-answering | null | [
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| # IT5 Small for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele S... | [
"# IT5 Small for Question Answering ⁉️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gab... | [
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text2text-generation | transformers | # IT5 Small for Question Generation 💭 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on question generation on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Text-to-t... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "question-generation", "squad_it", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Le conoscenze mediche erano stagnanti durante il Medioevo. Il resoconto pi\u00f9 autorev... | it5/it5-small-question-generation | null | [
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| # IT5 Small for Question Generation 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on question generation on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and Ma... | [
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"# IT5 Small for Question G... |
text2text-generation | transformers | # IT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/it5-small-repubblica-to-ilgiornale | null | [
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| # IT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
"# IT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: La... | [
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... |
summarization | transformers | # IT5 Small for Wikipedia Summarization ✂️📑 🇮🇹
This repository contains the checkpoint for the [IT5 Small](https://huggingface.co/gsarti/it5-small) model fine-tuned on Wikipedia summarization on the [WITS](https://www.semanticscholar.org/paper/WITS%3A-Wikipedia-for-Italian-Text-Summarization-Casola-Lavelli/ad6c8312... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "wikipedia", "summarization", "wits"], "datasets": ["wits"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "La 5\u00aa Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del p... | it5/it5-small-wiki-summarization | null | [
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| # IT5 Small for Wikipedia Summarization ️ 🇮🇹
This repository contains the checkpoint for the IT5 Small model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti ... | [
"# IT5 Small for Wikipedia Summarization ️ 🇮🇹\n\nThis repository contains the checkpoint for the IT5 Small model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele... | [
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"# IT5 Small for Wikipedia Sum... |
text2text-generation | transformers |
# mT5 Base for Formal-to-informal Style Transfer 🤗
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to-te... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Questa performance \u00e8 a dir poco spiacevole."}, {"text": "In attesa di un Suo cortese ris... | it5/mt5-base-formal-to-informal | null | [
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|
# mT5 Base for Formal-to-informal Style Transfer
This repository contains the checkpoint for the mT5 Base model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understan... | [
"# mT5 Base for Formal-to-informal Style Transfer \n\nThis repository contains the checkpoint for the mT5 Base model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Und... | [
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text2text-generation | transformers | # mT5 Base for News Headline Generation 📣 🇮🇹
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper [IT5: Large-scale Text-to-text Pretraining for Italia... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "headline-generation"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa deg... | it5/mt5-base-headline-generation | null | [
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| # mT5 Base for News Headline Generation 🇮🇹
This repository contains the checkpoint for the mT5 Base model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Ga... | [
"# mT5 Base for News Headline Generation 🇮🇹\n\nThis repository contains the checkpoint for the mT5 Base model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generatio... | [
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text2text-generation | transformers | # mT5 Base for News Headline Style Transfer (Il Giornale to Repubblica) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part o... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/mt5-base-ilgiornale-to-repubblica | null | [
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| # mT5 Base for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹
This repository contains the checkpoint for the mT5 Base model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-scale... | [
"# mT5 Base for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹\n\nThis repository contains the checkpoint for the mT5 Base model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Larg... | [
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... |
text2text-generation | transformers |
# mT5 Base for Informal-to-formal Style Transfer 🧐
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to-te... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "maronn qualcuno mi spieg' CHECCOSA SUCCEDE?!?!"}, {"text": "wellaaaaaaa, ma frat\u00e9 sei pr... | it5/mt5-base-informal-to-formal | null | [
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|
# mT5 Base for Informal-to-formal Style Transfer
This repository contains the checkpoint for the mT5 Base model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understan... | [
"# mT5 Base for Informal-to-formal Style Transfer \n\nThis repository contains the checkpoint for the mT5 Base model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Und... | [
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summarization | transformers | # mT5 Base for News Summarization ✂️🗞️ 🇮🇹
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on news summarization on the [Fanpage](https://huggingface.co/datasets/ARTeLab/fanpage) and [Il Post](https://huggingface.co/datasets/ARTeLab/ilpost) corpora ... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "fanpage", "ilpost", "summarization"], "datasets": ["ARTeLab/fanpage", "ARTeLab/ilpost"], "metrics": ["rouge"], "widget": [{"text": "Non lo vuole sposare. E\u2019 quanto emerge all\u2019interno dell\u2019ultima intervista di Raffa... | it5/mt5-base-news-summarization | null | [
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| # mT5 Base for News Summarization ️️ 🇮🇹
This repository contains the checkpoint for the mT5 Base model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sa... | [
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text2text-generation | transformers | # mT5 Base for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on extractive question answering on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Tex... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "squad_it", "text2text-question-answering", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["f1", "exact-match"], "widget": [{"text": "In seguito all' evento di estinzione del Cretaceo-Paleogene, l' estinzione dei d... | it5/mt5-base-question-answering | null | [
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| # mT5 Base for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the mT5 Base model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sar... | [
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text2text-generation | transformers | # mT5 Base for Question Generation 💭 🇮🇹
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on question generation on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Text-to-text... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "question-generation", "squad_it", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Le conoscenze mediche erano stagnanti durante il Medioevo. Il resoconto pi\u00f9 autorev... | it5/mt5-base-question-generation | null | [
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| # mT5 Base for Question Generation 🇮🇹
This repository contains the checkpoint for the mT5 Base model fine-tuned on question generation on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and Malv... | [
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text2text-generation | transformers | # mT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/mt5-base-repubblica-to-ilgiornale | null | [
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| # mT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
"# mT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹\n\nThis repository contains the checkpoint for the mT5 Small model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: La... | [
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... |
summarization | transformers | # mT5 Base for Wikipedia Summarization ✂️📑 🇮🇹
This repository contains the checkpoint for the [mT5 Base](https://huggingface.co/google/mt5-base) model fine-tuned on Wikipedia summarization on the [WITS](https://www.semanticscholar.org/paper/WITS%3A-Wikipedia-for-Italian-Text-Summarization-Casola-Lavelli/ad6c83122e7... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "wikipedia", "summarization", "wits"], "datasets": ["wits"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "La 5\u00aa Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del p... | it5/mt5-base-wiki-summarization | null | [
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| # mT5 Base for Wikipedia Summarization ️ 🇮🇹
This repository contains the checkpoint for the mT5 Base model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti an... | [
"# mT5 Base for Wikipedia Summarization ️ 🇮🇹\n\nThis repository contains the checkpoint for the mT5 Base model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele S... | [
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"# mT5 Base for Wikipedia Sum... |
text2text-generation | transformers |
# mT5 Small for Formal-to-informal Style Transfer 🤗
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Questa performance \u00e8 a dir poco spiacevole."}, {"text": "In attesa di un Suo cortese ris... | it5/mt5-small-formal-to-informal | null | [
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|
# mT5 Small for Formal-to-informal Style Transfer
This repository contains the checkpoint for the mT5 Small model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Underst... | [
"# mT5 Small for Formal-to-informal Style Transfer \n\nThis repository contains the checkpoint for the mT5 Small model fine-tuned on Formal-to-informal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language U... | [
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text2text-generation | transformers | # mT5 Small for News Headline Generation 📣 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper [IT5: Large-scale Text-to-text Pretraining for Ita... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "headline-generation"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "WASHINGTON - La Corea del Nord torna dopo nove anni nella blacklist Usa deg... | it5/mt5-small-headline-generation | null | [
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| # mT5 Small for News Headline Generation 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by ... | [
"# mT5 Small for News Headline Generation 🇮🇹\n\nThis repository contains the checkpoint for the mT5 Small model fine-tuned on news headline generation on the Italian HeadGen-IT dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generat... | [
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text2text-generation | transformers | # mT5 Small for News Headline Style Transfer (Il Giornale to Repubblica) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/mt5-small-ilgiornale-to-repubblica | null | [
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| # mT5 Small for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
"# mT5 Small for News Headline Style Transfer (Il Giornale to Repubblica) ️️️ 🇮🇹\n\nThis repository contains the checkpoint for the mT5 Small model fine-tuned on news headline style transfer in the Il Giornale to Repubblica direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: La... | [
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... |
text2text-generation | transformers |
# mT5 Small for Informal-to-formal Style Transfer 🧐
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper [IT5: Large-scale Text-to... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "style-transfer", "formality-style-transfer"], "datasets": ["yahoo/xformal_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "maronn qualcuno mi spieg' CHECCOSA SUCCEDE?!?!"}, {"text": "wellaaaaaaa, ma frat\u00e9 sei pr... | it5/mt5-small-informal-to-formal | null | [
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|
# mT5 Small for Informal-to-formal Style Transfer
This repository contains the checkpoint for the mT5 Small model fine-tuned on Informal-to-formal style transfer on the Italian subset of the XFORMAL dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Underst... | [
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summarization | transformers | # mT5 Small for News Summarization ✂️🗞️ 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on news summarization on the [Fanpage](https://huggingface.co/datasets/ARTeLab/fanpage) and [Il Post](https://huggingface.co/datasets/ARTeLab/ilpost) corpo... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "fanpage", "ilpost", "summarization"], "datasets": ["ARTeLab/fanpage", "ARTeLab/ilpost"], "metrics": ["rouge"], "widget": [{"text": "Non lo vuole sposare. E\u2019 quanto emerge all\u2019interno dell\u2019ultima intervista di Raffa... | it5/mt5-small-news-summarization | null | [
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| # mT5 Small for News Summarization ️️ 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on news summarization on the Fanpage and Il Post corpora as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele ... | [
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text2text-generation | transformers | # mT5 Small for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on extractive question answering on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale ... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "squad_it", "text2text-question-answering", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["f1", "exact-match"], "widget": [{"text": "In seguito all' evento di estinzione del Cretaceo-Paleogene, l' estinzione dei d... | it5/mt5-small-question-answering | null | [
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| # mT5 Small for Question Answering ⁉️ 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on extractive question answering on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele S... | [
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text2text-generation | transformers | # mT5 Small for Question Generation 💭 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on question generation on the [SQuAD-IT corpus](https://huggingface.co/datasets/squad_it) as part of the experiments of the paper [IT5: Large-scale Text-to-t... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "question-generation", "squad_it", "text2text-generation"], "datasets": ["squad_it"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "Le conoscenze mediche erano stagnanti durante il Medioevo. Il resoconto pi\u00f9 autorev... | it5/mt5-small-question-generation | null | [
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| # mT5 Small for Question Generation 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on question generation on the SQuAD-IT corpus as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti and Ma... | [
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"# mT5 Small for Question ... |
text2text-generation | transformers | # mT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) 🗞️➡️🗞️ 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as par... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "newspaper", "ilgiornale", "repubblica", "style-transfer"], "datasets": ["gsarti/change_it"], "metrics": ["rouge", "bertscore", "headline-headline-consistency-classifier", "headline-article-consistency-classifier"], "widget": [{"t... | it5/mt5-small-repubblica-to-ilgiornale | null | [
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| # mT5 Small for News Headline Style Transfer (Repubblica to Il Giornale) ️️️ 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on news headline style transfer in the Repubblica to Il Giornale direction on the Italian CHANGE-IT dataset as part of the experiments of the paper IT5: Large-sca... | [
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... |
summarization | transformers | # mT5 Small for Wikipedia Summarization ✂️📑 🇮🇹
This repository contains the checkpoint for the [mT5 Small](https://huggingface.co/google/mt5-small) model fine-tuned on Wikipedia summarization on the [WITS](https://www.semanticscholar.org/paper/WITS%3A-Wikipedia-for-Italian-Text-Summarization-Casola-Lavelli/ad6c8312... | {"language": ["it"], "license": "apache-2.0", "tags": ["italian", "sequence-to-sequence", "wikipedia", "summarization", "wits"], "datasets": ["wits"], "metrics": ["rouge", "bertscore"], "widget": [{"text": "La 5\u00aa Commissione ha competenza per i disegni di legge riguardanti le specifiche materie del bilancio, del p... | it5/mt5-small-wiki-summarization | null | [
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| # mT5 Small for Wikipedia Summarization ️ 🇮🇹
This repository contains the checkpoint for the mT5 Small model fine-tuned on Wikipedia summarization on the WITS dataset as part of the experiments of the paper IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation by Gabriele Sarti ... | [
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fill-mask | transformers | Note that model type is Camembert.
| {} | itsunoda/wolfbbsRoBERTa-small | null | [
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| Note that model type is Camembert.
| [] | [
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] |
null | transformers |
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with WordPiece masking).
We have shown that the standard BERT recipe (including model architecture ... | {"license": "apache-2.0", "thumbnail": "https://huggingface.co/front/thumbnails/google.png"} | iuliaturc/bert_uncased_L-2_H-128_A-2 | null | [
"transformers",
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1908.08962"
] | [] | TAGS
#transformers #pytorch #jax #bert #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us
| BERT Miniatures
===============
This is the set of 24 BERT models referenced in Well-Read Students Learn Better: On the Importance of Pre-training Compact Models (English only, uncased, trained with WordPiece masking).
We have shown that the standard BERT recipe (including model architecture and training objective)... | [] | [
"TAGS\n#transformers #pytorch #jax #bert #arxiv-1908.08962 #license-apache-2.0 #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers |
# Wav2Vec2-Large-XLSR-53-euskera
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Euskera using the [Common Voice](https://huggingface.co/datasets/common_voice).
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can ... | {"language": "eu", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["common_voice"], "model-index": [{"name": "XLSR Wav2Vec2 Basque Ivan G Torre", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "data... | ivangtorre/wav2vec2-large-xlsr-53-basque | null | [
"transformers",
"wav2vec2",
"automatic-speech-recognition",
"audio",
"speech",
"xlsr-fine-tuning-week",
"eu",
"dataset:common_voice",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"eu"
] | TAGS
#transformers #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #eu #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# Wav2Vec2-Large-XLSR-53-euskera
Fine-tuned facebook/wav2vec2-large-xlsr-53 in Euskera using the Common Voice.
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as f... | [
"# Wav2Vec2-Large-XLSR-53-euskera\nFine-tuned facebook/wav2vec2-large-xlsr-53 in Euskera using the Common Voice.\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## Usage\n\nThe model can be used directly (without a language model) as follows:",
"## Evaluation\n\nThe model can be... | [
"TAGS\n#transformers #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #eu #dataset-common_voice #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"# Wav2Vec2-Large-XLSR-53-euskera\nFine-tuned facebook/wav2vec2-large-xlsr-53 in Euskera using the Common Voice.\nWhen... |
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. -->
# language-detection-fine-tuned-on-xlm-roberta-base
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.c... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["common_language"], "metrics": ["accuracy"], "model-index": [{"name": "language-detection-fine-tuned-on-xlm-roberta-base", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "common_language", "type... | ivanlau/language-detection-fine-tuned-on-xlm-roberta-base | null | [
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"xlm-roberta",
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"license:mit",
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"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #dataset-common_language #license-mit #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
| language-detection-fine-tuned-on-xlm-roberta-base
=================================================
This model is a fine-tuned version of xlm-roberta-base on the common\_language dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1886
* Accuracy: 0.9738
### Training hyperparameters
The ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 1\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps: ... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:... |
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 [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on th... | {"language": ["zh"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "generated_from_trainer", "hf-asr-leaderboard", "mozilla-foundation/common_voice_8_0", "robust-speech-event", "zh-HK"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "XLS-R-300M - Chinese_HongKong (Can... | ivanlau/wav2vec2-large-xls-r-300m-cantonese | null | [
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"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"zh-HK",
"zh",
"dataset:mozilla-foundation/common_voice_8_0",
"license:apache-2.0",
"model-index",
"endpoints... | null | 2022-03-02T23:29:05+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #zh-HK #zh #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - ZH-HK dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4848
* Wer: 0.8004
Model description
-----------------
More information needed
Intended uses & limitations
-------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 16\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 64\n* optimizer: Adam with betas=(0.9,0.999) and epsilo... | [
"TAGS\n#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #hf-asr-leaderboard #mozilla-foundation/common_voice_8_0 #robust-speech-event #zh-HK #zh #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us \n",
"### Training h... |
question-answering | transformers |
# SciBERT-SQuAD-QuAC
This is the [SciBERT language representation model](https://huggingface.co/allenai/scibert_scivocab_uncased) fine tuned for Question Answering. SciBERT is a pre-trained language model based on BERT that has been trained on a large corpus of scientific text. When fine tuning for Question Answering... | {"language": "en"} | ixa-ehu/SciBERT-SQuAD-QuAC | null | [
"transformers",
"pytorch",
"safetensors",
"bert",
"question-answering",
"en",
"arxiv:1808.07036",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1808.07036"
] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #bert #question-answering #en #arxiv-1808.07036 #endpoints_compatible #has_space #region-us
|
# SciBERT-SQuAD-QuAC
This is the SciBERT language representation model fine tuned for Question Answering. SciBERT is a pre-trained language model based on BERT that has been trained on a large corpus of scientific text. When fine tuning for Question Answering we combined SQuAD2.0 and QuAC datasets.
If using this mod... | [
"# SciBERT-SQuAD-QuAC\n\nThis is the SciBERT language representation model fine tuned for Question Answering. SciBERT is a pre-trained language model based on BERT that has been trained on a large corpus of scientific text. When fine tuning for Question Answering we combined SQuAD2.0 and QuAC datasets.\n\nIf using ... | [
"TAGS\n#transformers #pytorch #safetensors #bert #question-answering #en #arxiv-1808.07036 #endpoints_compatible #has_space #region-us \n",
"# SciBERT-SQuAD-QuAC\n\nThis is the SciBERT language representation model fine tuned for Question Answering. SciBERT is a pre-trained language model based on BERT that has b... |
feature-extraction | transformers |
# BERTeus base cased
This is the Basque language pretrained model presented in [Give your Text Representation Models some Love: the Case for Basque](https://arxiv.org/pdf/2004.00033.pdf). This model has been trained on a Basque corpus comprising Basque crawled news articles from online newspapers and the Basque Wikip... | {"language": "eu"} | ixa-ehu/berteus-base-cased | null | [
"transformers",
"pytorch",
"jax",
"safetensors",
"bert",
"feature-extraction",
"eu",
"arxiv:2004.00033",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2004.00033"
] | [
"eu"
] | TAGS
#transformers #pytorch #jax #safetensors #bert #feature-extraction #eu #arxiv-2004.00033 #endpoints_compatible #region-us
| BERTeus base cased
==================
This is the Basque language pretrained model presented in Give your Text Representation Models some Love: the Case for Basque. This model has been trained on a Basque corpus comprising Basque crawled news articles from online newspapers and the Basque Wikipedia. The training corp... | [] | [
"TAGS\n#transformers #pytorch #jax #safetensors #bert #feature-extraction #eu #arxiv-2004.00033 #endpoints_compatible #region-us \n"
] |
null | transformers |
# IXAmBERT base cased
This is a multilingual language pretrained for English, Spanish and Basque. The training corpora is composed by the English, Spanish and Basque Wikipedias, together with Basque crawled news articles from online newspapers. The model has been successfully used to transfer knowledge from English t... | {"language": ["en", "es", "eu", "multilingual"]} | ixa-ehu/ixambert-base-cased | null | [
"transformers",
"pytorch",
"en",
"es",
"eu",
"multilingual",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en",
"es",
"eu",
"multilingual"
] | TAGS
#transformers #pytorch #en #es #eu #multilingual #endpoints_compatible #region-us
| IXAmBERT base cased
===================
This is a multilingual language pretrained for English, Spanish and Basque. The training corpora is composed by the English, Spanish and Basque Wikipedias, together with Basque crawled news articles from online newspapers. The model has been successfully used to transfer knowle... | [] | [
"TAGS\n#transformers #pytorch #en #es #eu #multilingual #endpoints_compatible #region-us \n"
] |
fill-mask | transformers |
# BERT small Japanese finance
This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
The model archi... | {"language": "ja", "license": "cc-by-sa-4.0", "tags": ["finance"], "widget": [{"text": "\u6d41\u52d5[MASK]\u306f\u30011\u5104\u5186\u3068\u306a\u308a\u307e\u3057\u305f\u3002"}]} | izumi-lab/bert-small-japanese-fin | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"finance",
"ja",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #bert #fill-mask #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# BERT small Japanese finance
This is a BERT model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as BERT small in the original ELECTRA paper; 12 layers, 256 dimensions of hidden sta... | [
"# BERT small Japanese finance\n\nThis is a BERT model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as BERT small in the original ELECTRA paper; 12 layers, 256 dimensions... | [
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"# BERT small Japanese finance\n\nThis is a BERT model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at ret... |
fill-mask | transformers |
# BERT small Japanese finance
This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
The model archi... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/bert-small-japanese | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #bert #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# BERT small Japanese finance
This is a BERT model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as BERT small in the original ELECTRA paper; 12 layers, 256 dimensions of hidden sta... | [
"# BERT small Japanese finance\n\nThis is a BERT model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as BERT small in the original ELECTRA paper; 12 layers, 256 dimensions... | [
"TAGS\n#transformers #pytorch #bert #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# BERT small Japanese finance\n\nThis is a BERT model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are availa... |
null | transformers |
# ELECTRA base Japanese discriminator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
T... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/electra-base-japanese-discriminator | null | [
"transformers",
"pytorch",
"electra",
"pretraining",
"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #electra #pretraining #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us
|
# ELECTRA base Japanese discriminator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA base in the original ELECTRA paper; 12 layers, 768 dimensions ... | [
"# ELECTRA base Japanese discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA base in the original ELECTRA paper; 12 layers, 7... | [
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"# ELECTRA base Japanese discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at... |
fill-mask | transformers |
# ELECTRA base Japanese generator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
The m... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/electra-base-japanese-generator | null | [
"transformers",
"pytorch",
"safetensors",
"electra",
"fill-mask",
"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #safetensors #electra #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# ELECTRA base Japanese generator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA base in the original ELECTRA implementation; 12 layers, 256 dimens... | [
"# ELECTRA base Japanese generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA base in the original ELECTRA implementation; 12 laye... | [
"TAGS\n#transformers #pytorch #safetensors #electra #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# ELECTRA base Japanese generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the... |
null | transformers |
# ELECTRA small Japanese discriminator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/electra-small-japanese-discriminator | null | [
"transformers",
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"electra",
"pretraining",
"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #electra #pretraining #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us
|
# ELECTRA small Japanese discriminator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA implementation; 12 layers, 256 ... | [
"# ELECTRA small Japanese discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA implementation; 1... | [
"TAGS\n#transformers #pytorch #electra #pretraining #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available a... |
null | transformers |
# ELECTRA small Japanese finance discriminator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model archit... | {"language": "ja", "license": "cc-by-sa-4.0", "tags": ["finance"], "widget": [{"text": "\u6d41\u52d5[MASK]\u306f1\u5104\u5186\u3068\u306a\u308a\u307e\u3057\u305f\u3002"}]} | izumi-lab/electra-small-japanese-fin-discriminator | null | [
"transformers",
"pytorch",
"electra",
"pretraining",
"finance",
"ja",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #electra #pretraining #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us
|
# ELECTRA small Japanese finance discriminator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA implementation; 12 laye... | [
"# ELECTRA small Japanese finance discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA implement... | [
"TAGS\n#transformers #pytorch #electra #pretraining #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese finance discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at ... |
fill-mask | transformers |
# ELECTRA small Japanese finance generator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architectu... | {"language": "ja", "license": "cc-by-sa-4.0", "tags": ["finance"], "widget": [{"text": "\u6d41\u52d5[MASK]\u306f1\u5104\u5186\u3068\u306a\u308a\u307e\u3057\u305f\u3002"}]} | izumi-lab/electra-small-japanese-fin-generator | null | [
"transformers",
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"safetensors",
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"finance",
"ja",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #safetensors #electra #fill-mask #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# ELECTRA small Japanese finance generator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA implementation; 12 layers, ... | [
"# ELECTRA small Japanese finance generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA implementatio... | [
"TAGS\n#transformers #pytorch #safetensors #electra #fill-mask #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese finance generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the ... |
fill-mask | transformers |
# ELECTRA small Japanese generator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
The ... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/electra-small-japanese-generator | null | [
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"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #safetensors #electra #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# ELECTRA small Japanese generator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA implementation; 12 layers, 256 dime... | [
"# ELECTRA small Japanese generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA implementation; 12 la... | [
"TAGS\n#transformers #pytorch #safetensors #electra #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for th... |
null | transformers |
# ELECTRA small Japanese discriminator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/electra-small-paper-japanese-discriminator | null | [
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"electra",
"pretraining",
"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #electra #pretraining #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us
|
# ELECTRA small Japanese discriminator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 layers, 256 dimension... | [
"# ELECTRA small Japanese discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 layers,... | [
"TAGS\n#transformers #pytorch #electra #pretraining #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available a... |
null | transformers |
# ELECTRA small Japanese finance discriminator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model archit... | {"language": "ja", "license": "cc-by-sa-4.0", "tags": ["finance"], "widget": [{"text": "\u6d41\u52d5[MASK]\u306f1\u5104\u5186\u3068\u306a\u308a\u307e\u3057\u305f\u3002"}]} | izumi-lab/electra-small-paper-japanese-fin-discriminator | null | [
"transformers",
"pytorch",
"electra",
"pretraining",
"finance",
"ja",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #electra #pretraining #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us
|
# ELECTRA small Japanese finance discriminator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 layers, 256 d... | [
"# ELECTRA small Japanese finance discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA paper; 12... | [
"TAGS\n#transformers #pytorch #electra #pretraining #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese finance discriminator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at ... |
fill-mask | transformers |
# ELECTRA small Japanese finance generator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architectu... | {"language": "ja", "license": "cc-by-sa-4.0", "tags": ["finance"], "widget": [{"text": "\u6d41\u52d5[MASK]\u306f1\u5104\u5186\u3068\u306a\u308a\u307e\u3057\u305f\u3002"}]} | izumi-lab/electra-small-paper-japanese-fin-generator | null | [
"transformers",
"pytorch",
"safetensors",
"electra",
"fill-mask",
"finance",
"ja",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #safetensors #electra #fill-mask #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# ELECTRA small Japanese finance generator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 layers, 64 dimens... | [
"# ELECTRA small Japanese finance generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 lay... | [
"TAGS\n#transformers #pytorch #safetensors #electra #fill-mask #finance #ja #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese finance generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the ... |
fill-mask | transformers |
# ELECTRA small Japanese generator
This is a [ELECTRA](https://github.com/google-research/electra) model pretrained on texts in the Japanese language.
The codes for the pretraining are available at [retarfi/language-pretraining](https://github.com/retarfi/language-pretraining/tree/v1.0).
## Model architecture
The ... | {"language": "ja", "license": "cc-by-sa-4.0", "datasets": ["wikipedia"], "widget": [{"text": "\u6771\u4eac\u5927\u5b66\u3067[MASK]\u306e\u7814\u7a76\u3092\u3057\u3066\u3044\u307e\u3059\u3002"}]} | izumi-lab/electra-small-paper-japanese-generator | null | [
"transformers",
"pytorch",
"safetensors",
"electra",
"fill-mask",
"ja",
"dataset:wikipedia",
"arxiv:2003.10555",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2003.10555"
] | [
"ja"
] | TAGS
#transformers #pytorch #safetensors #electra #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us
|
# ELECTRA small Japanese generator
This is a ELECTRA model pretrained on texts in the Japanese language.
The codes for the pretraining are available at retarfi/language-pretraining.
## Model architecture
The model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 layers, 64 dimensions of ... | [
"# ELECTRA small Japanese generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for the pretraining are available at retarfi/language-pretraining.",
"## Model architecture\n\nThe model architecture is the same as ELECTRA small in the original ELECTRA paper; 12 layers, 64 ... | [
"TAGS\n#transformers #pytorch #safetensors #electra #fill-mask #ja #dataset-wikipedia #arxiv-2003.10555 #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# ELECTRA small Japanese generator\n\nThis is a ELECTRA model pretrained on texts in the Japanese language.\n\nThe codes for th... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-base-timit-demo-colab
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wa... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-timit-demo-colab", "results": []}]} | izzy-lazerson/wav2vec2-base-timit-demo-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"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 #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-base-timit-demo-colab
==============================
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4545
* Wer: 0.3450
Model description
-----------------
More information needed
Intended uses & limi... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 32\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
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"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0001\n* train\\_batch\\_size: 3... |
automatic-speech-recognition | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-xls-r-300m-turkish-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["common_voice"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-turkish-colab", "results": []}]} | izzy-lazerson/wav2vec2-large-xls-r-300m-turkish-colab | null | [
"transformers",
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:common_voice",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us
| wav2vec2-large-xls-r-300m-turkish-colab
=======================================
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common\_voice dataset.
It achieves the following results on the evaluation set:
* Loss: 0.3866
* Wer: 0.3363
Model description
-----------------
More informat... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 32\n* optimizer: Adam with betas=(0.9,0.999) and epsilon... | [
"TAGS\n#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-common_voice #license-apache-2.0 #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0003\n* t... |
text-classification | transformers |
# Emotion English DistilRoBERTa-base
# Description ℹ
With this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets (see Appendix below) and predicts Ekman's 6 basic emotions, plus a neutral class:
1) anger 🤬
2) disgust 🤢
3) fear 😨
4) joy 😀
5) neutral 😐
6) sadness ... | {"language": "en", "tags": ["distilroberta", "sentiment", "emotion", "twitter", "reddit"], "widget": [{"text": "Oh wow. I didn't know that."}, {"text": "This movie always makes me cry.."}, {"text": "Oh Happy Day"}]} | j-hartmann/emotion-english-distilroberta-base | null | [
"transformers",
"pytorch",
"tf",
"roberta",
"text-classification",
"distilroberta",
"sentiment",
"emotion",
"twitter",
"reddit",
"en",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #tf #roberta #text-classification #distilroberta #sentiment #emotion #twitter #reddit #en #autotrain_compatible #endpoints_compatible #has_space #region-us
| Emotion English DistilRoBERTa-base
==================================
Description ℹ
=============
With this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets (see Appendix below) and predicts Ekman's 6 basic emotions, plus a neutral class:
1. anger
2. disgust
3. fe... | [] | [
"TAGS\n#transformers #pytorch #tf #roberta #text-classification #distilroberta #sentiment #emotion #twitter #reddit #en #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
text-classification | transformers |
## Description ℹ
With this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets and predicts Ekman's 6 basic emotions, plus a neutral class:
1) anger 🤬
2) disgust 🤢
3) fear 😨
4) joy 😀
5) neutral 😐
6) sadness 😭
7) surprise 😲
The model is a fine-tuned checkpoint of... | {"language": "en", "tags": ["roberta", "sentiment", "emotion", "twitter", "reddit"], "widget": [{"text": "Oh wow. I didn't know that."}, {"text": "This movie always makes me cry.."}, {"text": "Oh Happy Day"}]} | j-hartmann/emotion-english-roberta-large | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"sentiment",
"emotion",
"twitter",
"reddit",
"en",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #roberta #text-classification #sentiment #emotion #twitter #reddit #en #autotrain_compatible #endpoints_compatible #has_space #region-us
|
## Description ℹ
With this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets and predicts Ekman's 6 basic emotions, plus a neutral class:
1) anger
2) disgust
3) fear
4) joy
5) neutral
6) sadness
7) surprise
The model is a fine-tuned checkpoint of RoBERTa-large... | [
"## Description ℹ\n\nWith this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets and predicts Ekman's 6 basic emotions, plus a neutral class:\n\n1) anger \n2) disgust \n3) fear \n4) joy \n5) neutral \n6) sadness \n7) surprise \n\nThe model is a fine-tuned checkpoint ... | [
"TAGS\n#transformers #pytorch #roberta #text-classification #sentiment #emotion #twitter #reddit #en #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"## Description ℹ\n\nWith this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets and predicts... |
text-classification | transformers |
This RoBERTa-based model ("MindMiner") can classify the degree of mind perception in English language text in 2 classes:
- high mind perception 👩
- low mind perception 🤖
The model was fine-tuned on 997 manually annotated open-ended survey responses.
The hold-out accuracy is 75.5% (vs. a balanced 50% random-chance... | {"language": "en", "tags": ["roberta"], "widget": [{"text": "Alexa is part of our family. She is simply amazing!"}, {"text": "I use my smart assistant for may things. It's incredibly useful."}]} | j-hartmann/MindMiner-Binary | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"en",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #roberta #text-classification #en #autotrain_compatible #endpoints_compatible #has_space #region-us
|
This RoBERTa-based model ("MindMiner") can classify the degree of mind perception in English language text in 2 classes:
- high mind perception
- low mind perception
The model was fine-tuned on 997 manually annotated open-ended survey responses.
The hold-out accuracy is 75.5% (vs. a balanced 50% random-chance bas... | [] | [
"TAGS\n#transformers #pytorch #roberta #text-classification #en #autotrain_compatible #endpoints_compatible #has_space #region-us \n"
] |
text-classification | transformers |
This RoBERTa-based model can classify *expressed purchase intentions* in English language text in 2 classes:
- purchase intention 🤩
- no purchase intention 😐
The model was fine-tuned on 2,000 manually annotated social media posts.
The hold-out accuracy is 95% (vs. a balanced 50% random-chance baseline).
For deta... | {"language": "en", "tags": ["roberta", "sentiment", "twitter"], "widget": [{"text": "This looks tasty. Where can I buy it??"}, {"text": "Now I want this, too."}, {"text": "You look great today!"}, {"text": "I just love spring and sunshine!"}]} | j-hartmann/purchase-intention-english-roberta-large | null | [
"transformers",
"pytorch",
"roberta",
"text-classification",
"sentiment",
"twitter",
"en",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #roberta #text-classification #sentiment #twitter #en #autotrain_compatible #endpoints_compatible #region-us
|
This RoBERTa-based model can classify *expressed purchase intentions* in English language text in 2 classes:
- purchase intention
- no purchase intention
The model was fine-tuned on 2,000 manually annotated social media posts.
The hold-out accuracy is 95% (vs. a balanced 50% random-chance baseline).
For details ... | [
"# Application",
"# Reference\nPlease cite this paper when you use our model. Feel free to reach out to jochen.hartmann@URL with any questions or feedback you may have."
] | [
"TAGS\n#transformers #pytorch #roberta #text-classification #sentiment #twitter #en #autotrain_compatible #endpoints_compatible #region-us \n",
"# Application",
"# Reference\nPlease cite this paper when you use our model. Feel free to reach out to jochen.hartmann@URL with any questions or feedback you may have.... |
text-classification | transformers |
This RoBERTa-based model can classify the sentiment of English language text in 3 classes:
- positive 😀
- neutral 😐
- negative 🙁
The model was fine-tuned on 5,304 manually annotated social media posts.
The hold-out accuracy is 86.1%.
For details on the training approach see Web Appendix F in Hartmann et al. (20... | {"language": "en", "tags": ["roberta", "sentiment", "twitter"], "widget": [{"text": "Oh no. This is bad.."}, {"text": "To be or not to be."}, {"text": "Oh Happy Day"}]} | j-hartmann/sentiment-roberta-large-english-3-classes | null | [
"transformers",
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"roberta",
"text-classification",
"sentiment",
"twitter",
"en",
"autotrain_compatible",
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #roberta #text-classification #sentiment #twitter #en #autotrain_compatible #endpoints_compatible #has_space #region-us
|
This RoBERTa-based model can classify the sentiment of English language text in 3 classes:
- positive
- neutral
- negative
The model was fine-tuned on 5,304 manually annotated social media posts.
The hold-out accuracy is 86.1%.
For details on the training approach see Web Appendix F in Hartmann et al. (2021).
... | [
"# Application",
"# Reference\nPlease cite this paper when you use our model. Feel free to reach out to jochen.hartmann@URL with any questions or feedback you may have."
] | [
"TAGS\n#transformers #pytorch #roberta #text-classification #sentiment #twitter #en #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# Application",
"# Reference\nPlease cite this paper when you use our model. Feel free to reach out to jochen.hartmann@URL with any questions or feedback yo... |
null | null | # dummy file! | {} | j961224/dummy | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| # dummy file! | [
"# dummy file!"
] | [
"TAGS\n#region-us \n",
"# dummy file!"
] |
text-generation | transformers | skt/kogpt2-base-v2에 wellness 및 일상챗봇 데이터를 fine-tuning한 모델입니다. | {} | jack-oh/KoGPT2_finetuned_wellness | null | [
"transformers",
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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
| skt/kogpt2-base-v2에 wellness 및 일상챗봇 데이터를 fine-tuning한 모델입니다. | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
fill-mask | transformers |
# SecBERT
This is the pretrained model presented in [SecBERT: A Pretrained Language Model for Cyber Security Text](https://github.com/jackaduma/SecBERT/), which is a BERT model trained on cyber security text.
The training corpus was papers taken from
* [APTnotes](https://github.com/kbandla/APTnotes)
* [Stucco-Da... | {"language": "en", "license": "apache-2.0", "tags": ["exbert", "security", "cybersecurity", "cyber security", "threat hunting", "threat intelligence"], "datasets": ["APTnotes", "Stucco-Data", "CASIE"], "thumbnail": "https://github.com/jackaduma"} | jackaduma/SecBERT | null | [
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"threat intelligence",
"en",
"dataset:APTnotes",
"dataset:Stucco-Data",
"dataset:CASIE",
"license:apache-2.0",
"autotrain_compatible",
"endpoint... | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #bert #fill-mask #exbert #security #cybersecurity #cyber security #threat hunting #threat intelligence #en #dataset-APTnotes #dataset-Stucco-Data #dataset-CASIE #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# SecBERT
This is the pretrained model presented in SecBERT: A Pretrained Language Model for Cyber Security Text, which is a BERT model trained on cyber security text.
The training corpus was papers taken from
* APTnotes
* Stucco-Data: Cyber security data sources
* CASIE: Extracting Cybersecurity Event Informat... | [
"# SecBERT\n\nThis is the pretrained model presented in SecBERT: A Pretrained Language Model for Cyber Security Text, which is a BERT model trained on cyber security text.\n\nThe training corpus was papers taken from \n * APTnotes\n * Stucco-Data: Cyber security data sources\n * CASIE: Extracting Cybersecurity Even... | [
"TAGS\n#transformers #pytorch #safetensors #bert #fill-mask #exbert #security #cybersecurity #cyber security #threat hunting #threat intelligence #en #dataset-APTnotes #dataset-Stucco-Data #dataset-CASIE #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# SecBERT\n\nThis ... |
fill-mask | transformers |
# SecRoBERTa
This is the pretrained model presented in [SecBERT: A Pretrained Language Model for Cyber Security Text](https://github.com/jackaduma/SecBERT/), which is a SecRoBERTa model trained on cyber security text.
The training corpus was papers taken from
* [APTnotes](https://github.com/kbandla/APTnotes)
* [S... | {"language": "en", "license": "apache-2.0", "tags": ["exbert", "security", "cybersecurity", "cyber security", "threat hunting", "threat intelligence"], "datasets": ["APTnotes", "Stucco-Data", "CASIE"], "thumbnail": "https://github.com/jackaduma"} | jackaduma/SecRoBERTa | null | [
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"en",
"dataset:APTnotes",
"dataset:Stucco-Data",
"dataset:CASIE",
"license:apache-2.0",
"autotrain_compatible",
"endpo... | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #safetensors #roberta #fill-mask #exbert #security #cybersecurity #cyber security #threat hunting #threat intelligence #en #dataset-APTnotes #dataset-Stucco-Data #dataset-CASIE #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# SecRoBERTa
This is the pretrained model presented in SecBERT: A Pretrained Language Model for Cyber Security Text, which is a SecRoBERTa model trained on cyber security text.
The training corpus was papers taken from
* APTnotes
* Stucco-Data: Cyber security data sources
* CASIE: Extracting Cybersecurity Event ... | [
"# SecRoBERTa\n\nThis is the pretrained model presented in SecBERT: A Pretrained Language Model for Cyber Security Text, which is a SecRoBERTa model trained on cyber security text.\n\nThe training corpus was papers taken from \n * APTnotes\n * Stucco-Data: Cyber security data sources\n * CASIE: Extracting Cybersecu... | [
"TAGS\n#transformers #pytorch #safetensors #roberta #fill-mask #exbert #security #cybersecurity #cyber security #threat hunting #threat intelligence #en #dataset-APTnotes #dataset-Stucco-Data #dataset-CASIE #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# SecRoBERTa\n\... |
summarization | transformers | ## `bart-large-cnn-samsum`
This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
For more information look at:
- [🤗 Transformers Documentation: Amazon SageMaker](https://huggingface.co/transformers/sagemaker.html)
- [Example Notebooks](https://github.com/huggingface/notebooks/... | {"language": "en", "license": "apache-2.0", "tags": ["sagemaker", "bart", "summarization"], "datasets": ["samsum"], "widget": [{"text": "Jeff: Can I train a \ud83e\udd17 Transformers model on Amazon SageMaker? \nPhilipp: Sure you can use the new Hugging Face Deep Learning Container. \nJeff: ok.\nJeff: and how can I get... | jackieliu930/bart-large-cnn-samsum | null | [
"transformers",
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"bart",
"text2text-generation",
"sagemaker",
"summarization",
"en",
"dataset:samsum",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #bart #text2text-generation #sagemaker #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us
| 'bart-large-cnn-samsum'
-----------------------
This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
For more information look at:
* Transformers Documentation: Amazon SageMaker
* Example Notebooks
* Amazon SageMaker documentation for Hugging Face
* Python SDK SageMaker do... | [] | [
"TAGS\n#transformers #pytorch #bart #text2text-generation #sagemaker #summarization #en #dataset-samsum #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
# Jon Snow DialoGPT Model | {"tags": ["conversational"]} | jackky46/DialoGPT-medium-got | 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
|
# Jon Snow DialoGPT Model | [
"# Jon Snow DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Jon Snow DialoGPT Model"
] |
null | null | # Model Card
`blenderbot-small-tflite` is a tflite version of `blenderbot-small-90M` I converted for my UTA CSE3310 class. See the repo at [https://github.com/kmosoti/DesparadosAEYE](https://github.com/kmosoti/DesparadosAEYE) and the conversion process [here](https://drive.google.com/file/d/1F93nMsDIm1TWhn70FcLtcaKQUy... | {"language": "en", "license": "apache-2.0", "tags": ["Android", "tflite", "blenderbot"]} | jacob-valdez/blenderbot-small-tflite | null | [
"tflite",
"Android",
"blenderbot",
"en",
"license:apache-2.0",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#tflite #Android #blenderbot #en #license-apache-2.0 #region-us
| # Model Card
'blenderbot-small-tflite' is a tflite version of 'blenderbot-small-90M' I converted for my UTA CSE3310 class. See the repo at URL and the conversion process here.
You have to right pad your user and model input integers to make them [32,]-shaped. Then indicate te true length with the 3rd and 4th params.
... | [
"# Model Card\n\n'blenderbot-small-tflite' is a tflite version of 'blenderbot-small-90M' I converted for my UTA CSE3310 class. See the repo at URL and the conversion process here.\n\nYou have to right pad your user and model input integers to make them [32,]-shaped. Then indicate te true length with the 3rd and 4th... | [
"TAGS\n#tflite #Android #blenderbot #en #license-apache-2.0 #region-us \n",
"# Model Card\n\n'blenderbot-small-tflite' is a tflite version of 'blenderbot-small-90M' I converted for my UTA CSE3310 class. See the repo at URL and the conversion process here.\n\nYou have to right pad your user and model input integer... |
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. -->
# hackMIT-finetuned-sst2
This model is a fine-tuned version of [Blaine-Mason/hackMIT-finetuned-sst2](https://huggingface.co/Blaine... | {"tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy"], "model_index": [{"name": "hackMIT-finetuned-sst2", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "args": "sst2"}, "metric": {"name": "Accuracy", "type": ... | jacobduncan00/hackMIT-finetuned-sst2 | null | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-glue #autotrain_compatible #endpoints_compatible #region-us
| hackMIT-finetuned-sst2
======================
This model is a fine-tuned version of Blaine-Mason/hackMIT-finetuned-sst2 on the glue dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0046
* Accuracy: 0.7970
Model description
-----------------
More information needed
Intended uses & li... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1.7339491016138283e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 16\n* seed: 23\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: ... | [
"TAGS\n#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-glue #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 1.7339491016138283e-05\n* trai... |
question-answering | transformers |
# Danish BERT (version 2, uncased) by [BotXO](https://github.com/botxo/nordic_bert) fine-tuned for Question Answering (QA) on the [machine-translated SQuAD-da dataset](https://github.com/ccasimiro88/TranslateAlignRetrieve/tree/multilingual/squads-tar/da)
```python
from transformers import AutoTokenizer, AutoModelF... | {"language": "da", "license": "cc-by-4.0", "tags": ["danish", "bert", "question answering", "squad", "machine translation", "botxo"], "datasets": ["common_crawl", "wikipedia", "dindebat.dk", "hestenettet.dk", "danish OpenSubtitles"], "widget": [{"context": "Stine sagde hej, men Jacob sagde hall\u00f8j."}]} | jacobshein/danish-bert-botxo-qa-squad | null | [
"transformers",
"pytorch",
"bert",
"question-answering",
"danish",
"question answering",
"squad",
"machine translation",
"botxo",
"da",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"da"
] | TAGS
#transformers #pytorch #bert #question-answering #danish #question answering #squad #machine translation #botxo #da #license-cc-by-4.0 #endpoints_compatible #region-us
|
# Danish BERT (version 2, uncased) by BotXO fine-tuned for Question Answering (QA) on the machine-translated SQuAD-da dataset
#### Contact
For further information on usage or fine-tuning procedure, please reach out by email through URL.
| [
"# Danish BERT (version 2, uncased) by BotXO fine-tuned for Question Answering (QA) on the machine-translated SQuAD-da dataset",
"#### Contact\n\nFor further information on usage or fine-tuning procedure, please reach out by email through URL."
] | [
"TAGS\n#transformers #pytorch #bert #question-answering #danish #question answering #squad #machine translation #botxo #da #license-cc-by-4.0 #endpoints_compatible #region-us \n",
"# Danish BERT (version 2, uncased) by BotXO fine-tuned for Question Answering (QA) on the machine-translated SQuAD-da dataset",
"##... |
text-classification | transformers | # Usage
```python
# import library
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
# load model
tokenizer = AutoTokenizer.from_pretrained("jaehyeong/koelectra-base-v3-generalized-sentiment-analysis")
model = AutoModelForSequenceClassification.from_pre... | {} | Copycats/koelectra-base-v3-generalized-sentiment-analysis | null | [
"transformers",
"pytorch",
"safetensors",
"electra",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #safetensors #electra #text-classification #autotrain_compatible #endpoints_compatible #region-us
| # Usage
- label 0 : negative review
- label 1 : positive review | [
"# Usage\n\n\n- label 0 : negative review\n- label 1 : positive review"
] | [
"TAGS\n#transformers #pytorch #safetensors #electra #text-classification #autotrain_compatible #endpoints_compatible #region-us \n",
"# Usage\n\n\n- label 0 : negative review\n- label 1 : positive review"
] |
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... | jaesun/distilbert-base-uncased-finetuned-cola | null | [
"transformers",
"pytorch",
"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 #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: 0.8815
* Matthews Correlation: 0.5173
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 #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\\_rate: 2e-0... |
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. -->
# kcbert-base-finetuned-nsmc
This model is a fine-tuned version of [beomi/kcbert-base](https://huggingface.co/beomi/kcbert-base) o... | {"tags": ["generated_from_trainer"], "datasets": ["nsmc"], "metrics": ["accuracy", "f1", "recall", "precision"], "model-index": [{"name": "kcbert-base-finetuned-nsmc", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "nsmc", "type": "nsmc", "args": "default"}, "me... | jaesun/kcbert-base-finetuned-nsmc | null | [
"transformers",
"pytorch",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:nsmc",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-nsmc #model-index #autotrain_compatible #endpoints_compatible #region-us
| kcbert-base-finetuned-nsmc
==========================
This model is a fine-tuned version of beomi/kcbert-base on the nsmc dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4197
* Accuracy: 0.9020
* F1: 0.9033
* Recall: 0.9095
* Precision: 0.8972
Model description
-----------------
More... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3\n* mixed\\_prec... | [
"TAGS\n#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-nsmc #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size:... |
text-generation | transformers |
# FF8 DialoGPT Model | {"tags": ["conversational"]} | jahz/DialoGPT-medium-FF8 | 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
|
# FF8 DialoGPT Model | [
"# FF8 DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# FF8 DialoGPT Model"
] |
feature-extraction | transformers | tokenizer = AutoTokenizer.from_pretrained("jaimin/Gujarati-Model")
model = AutoModel.from_pretrained("jaimin/Gujarati-Model") | {} | jaimin/Gujarati-Model | null | [
"transformers",
"pytorch",
"roberta",
"feature-extraction",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #roberta #feature-extraction #endpoints_compatible #region-us
| tokenizer = AutoTokenizer.from_pretrained("jaimin/Gujarati-Model")
model = AutoModel.from_pretrained("jaimin/Gujarati-Model") | [] | [
"TAGS\n#transformers #pytorch #roberta #feature-extraction #endpoints_compatible #region-us \n"
] |
text-classification | transformers | "hello"
| {} | jaimin/plagiarism_checker | null | [
"transformers",
"pytorch",
"longformer",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #longformer #text-classification #autotrain_compatible #endpoints_compatible #region-us
| "hello"
| [] | [
"TAGS\n#transformers #pytorch #longformer #text-classification #autotrain_compatible #endpoints_compatible #region-us \n"
] |
automatic-speech-recognition | transformers |
# wav2vec2-base-gujarati-demo
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Guj
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
```python
import torc... | {"language": "Guj", "license": "apache-2.0", "tags": ["audio", "automatic-speech-recognition", "speech", "xlsr-fine-tuning-week"], "datasets": ["google"], "model-index": [{"name": "XLSR Wav2Vec2 Guj by Jaimin", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"nam... | jaimin/wav2vec2-base-gujarati-demo | null | [
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"xlsr-fine-tuning-week",
"dataset:google",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"Guj"
] | TAGS
#transformers #pytorch #jax #wav2vec2 #automatic-speech-recognition #audio #speech #xlsr-fine-tuning-week #dataset-google #license-apache-2.0 #model-index #endpoints_compatible #region-us
|
# wav2vec2-base-gujarati-demo
Fine-tuned facebook/wav2vec2-large-xlsr-53 in Guj
When using this model, make sure that your speech input is sampled at 16kHz.
## Usage
The model can be used directly (without a language model) as follows:
## Evaluation
The model can be evaluated as follows on the {language} test ... | [
"# wav2vec2-base-gujarati-demo\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 in Guj\nWhen using this model, make sure that your speech input is sampled at 16kHz.",
"## 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 ... | [
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"# wav2vec2-base-gujarati-demo\n\nFine-tuned facebook/wav2vec2-large-xlsr-53 in Guj\nWhen using this model, make s... |
text-classification | transformers | # CoronaCentral BERT Model for Topic / Article Type Classification
This is the topic / article type multi-label classification for the [CoronaCentral website](https://coronacentral.ai). This forms part of the pipeline for downloading and processing coronavirus literature described in the [corona-ml repo](https://githu... | {"language": "en", "license": "mit", "tags": ["coronavirus", "covid", "bionlp"], "datasets": ["cord19", "pubmed"], "thumbnail": "https://coronacentral.ai/logo-with-name.png?1", "widget": [{"text": "Pre-existing T-cell immunity to SARS-CoV-2 in unexposed healthy controls in Ecuador, as detected with a COVID-19 Interfero... | jakelever/coronabert | null | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"coronavirus",
"covid",
"bionlp",
"en",
"dataset:cord19",
"dataset:pubmed",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #tf #jax #bert #text-classification #coronavirus #covid #bionlp #en #dataset-cord19 #dataset-pubmed #license-mit #autotrain_compatible #endpoints_compatible #region-us
| # CoronaCentral BERT Model for Topic / Article Type Classification
This is the topic / article type multi-label classification for the CoronaCentral website. This forms part of the pipeline for downloading and processing coronavirus literature described in the corona-ml repo with available step-by-step descriptions. T... | [
"# CoronaCentral BERT Model for Topic / Article Type Classification\n\nThis is the topic / article type multi-label classification for the CoronaCentral website. This forms part of the pipeline for downloading and processing coronavirus literature described in the corona-ml repo with available step-by-step descript... | [
"TAGS\n#transformers #pytorch #tf #jax #bert #text-classification #coronavirus #covid #bionlp #en #dataset-cord19 #dataset-pubmed #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# CoronaCentral BERT Model for Topic / Article Type Classification\n\nThis is the topic / article type multi-l... |
text-to-speech | transformers |
# HiFi-GAN
[HiFi-GAN](https://arxiv.org/abs/2010.05646) vocoder trained on the [LJ Speech dataset](https://keithito.com/LJ-Speech-Dataset/). The modeling code is based on the [official implementation](https://github.com/jik876/hifi-gan) and the [fairseq adaptation](https://github.com/pytorch/fairseq).
## Usage
```p... | {"language": "en", "tags": ["audio", "text-to-speech"], "datasets": ["ljspeech"]} | jaketae/hifigan-lj-v1 | null | [
"transformers",
"pytorch",
"hifigan",
"feature-extraction",
"audio",
"text-to-speech",
"custom_code",
"en",
"dataset:ljspeech",
"arxiv:2010.05646",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"2010.05646"
] | [
"en"
] | TAGS
#transformers #pytorch #hifigan #feature-extraction #audio #text-to-speech #custom_code #en #dataset-ljspeech #arxiv-2010.05646 #region-us
|
# HiFi-GAN
HiFi-GAN vocoder trained on the LJ Speech dataset. The modeling code is based on the official implementation and the fairseq adaptation.
## Usage
| [
"# HiFi-GAN\n\nHiFi-GAN vocoder trained on the LJ Speech dataset. The modeling code is based on the official implementation and the fairseq adaptation.",
"## Usage"
] | [
"TAGS\n#transformers #pytorch #hifigan #feature-extraction #audio #text-to-speech #custom_code #en #dataset-ljspeech #arxiv-2010.05646 #region-us \n",
"# HiFi-GAN\n\nHiFi-GAN vocoder trained on the LJ Speech dataset. The modeling code is based on the official implementation and the fairseq adaptation.",
"## Usa... |
question-answering | transformers | XLM-RoBERTa base (`xlm-roberta-base`) finetuned on squad v1.1.
**Training-specifications:**
- training_epochs: 3.0
- max_seq_length: 384
- batch_size: 16
- dataset_name: squad
- doc_stride 128
**Train-results:**
```
{
"epoch": 3.0,
"init_mem_cpu_alloc_delta": 991453184,
"init_mem_cpu_peaked_delta": 0,... | {} | jakobwes/xlm_roberta_squad_v1.1 | null | [
"transformers",
"pytorch",
"xlm-roberta",
"question-answering",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #question-answering #endpoints_compatible #region-us
| XLM-RoBERTa base ('xlm-roberta-base') finetuned on squad v1.1.
Training-specifications:
- training_epochs: 3.0
- max_seq_length: 384
- batch_size: 16
- dataset_name: squad
- doc_stride 128
Train-results:
Eval-results:
| [] | [
"TAGS\n#transformers #pytorch #xlm-roberta #question-answering #endpoints_compatible #region-us \n"
] |
text-generation | transformers |
# jalenbot DialoGPT Model | {"tags": ["conversational"]} | jalensmh/DialoGPT-medium-jalenbot | 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
|
# jalenbot DialoGPT Model | [
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"# jalenbot DialoGPT Model"
] |
text-generation | transformers |
# exophoria DialoGPT Model | {"tags": ["conversational"]} | jalensmh/DialoGPT-small-exophoria | 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
|
# exophoria DialoGPT Model | [
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"# exophoria DialoGPT Model"
] |
question-answering | transformers |
This is the [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) model ([source](https://github.com/PlanTL-SANIDAD/lm-spanish)) trained on the [squad_es v2.0.0](https://huggingface.co/datasets/squad_es) dataset ([source](https://github.com/ccasimiro88/TranslateAlignRetrieve)).
Current achieve... | {"language": ["es"], "datasets": ["squad_es"], "widget": [{"text": "\u00bfQui\u00e9n era el duque en la batalla de Hastings?", "context": "La dinast\u00eda normanda tuvo un gran impacto pol\u00edtico, cultural y militar en la Europa medieval e incluso en el Cercano Oriente. Los normandos eran famosos por su esp\u00edri... | jamarju/roberta-base-bne-squad-2.0-es | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"es",
"dataset:squad_es",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #roberta #question-answering #es #dataset-squad_es #endpoints_compatible #region-us
|
This is the BSC-TeMU/roberta-base-bne model (source) trained on the squad_es v2.0.0 dataset (source).
Current achievement: em=58.80, f1=67.40
Results:
Training script:
| [] | [
"TAGS\n#transformers #pytorch #roberta #question-answering #es #dataset-squad_es #endpoints_compatible #region-us \n"
] |
question-answering | transformers |
This is the [BSC-TeMU/roberta-large-bne](https://huggingface.co/BSC-TeMU/roberta-large-bne) model ([source](https://github.com/PlanTL-SANIDAD/lm-spanish)) trained on the [squad_es v2.0.0](https://huggingface.co/datasets/squad_es) dataset ([source](https://github.com/ccasimiro88/TranslateAlignRetrieve)).
Current achie... | {"language": ["es"], "datasets": ["squad_es"], "widget": [{"text": "\u00bfQui\u00e9n era el duque en la batalla de Hastings?", "context": "La dinast\u00eda normanda tuvo un gran impacto pol\u00edtico, cultural y militar en la Europa medieval e incluso en el Cercano Oriente. Los normandos eran famosos por su esp\u00edri... | jamarju/roberta-large-bne-squad-2.0-es | null | [
"transformers",
"pytorch",
"roberta",
"question-answering",
"es",
"dataset:squad_es",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"es"
] | TAGS
#transformers #pytorch #roberta #question-answering #es #dataset-squad_es #endpoints_compatible #region-us
|
This is the BSC-TeMU/roberta-large-bne model (source) trained on the squad_es v2.0.0 dataset (source).
Current achievement: em=60.21, f1=68.61
Results:
Training script:
| [] | [
"TAGS\n#transformers #pytorch #roberta #question-answering #es #dataset-squad_es #endpoints_compatible #region-us \n"
] |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# marker-associations-binary-base
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-full... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["marker-associations-binary-base"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "marker-associations-binary-base", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name... | jambo/marker-associations-binary-base | null | [
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"dataset:marker-associations-binary-base",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-marker-associations-binary-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| marker-associations-binary-base
===============================
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the marker-associations-binary-base dataset.
It achieves the following results on the evaluation set:
### Gene Results
* Precision = 0.808
* Recall... | [
"### Gene Results\n\n\n* Precision = 0.808\n* Recall = 0.940\n* F1 = 0.869\n* Accuracy = 0.862\n* AUC = 0.944",
"### Chemical Results\n\n\n* Precision = 0.774\n* Recall = 1.0\n* F1 = 0.873\n* Accuracy = 0.926\n* AUC = 0.964\n\n\nModel description\n-----------------\n\n\nMore information needed\n\n\nIntended uses ... | [
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"### Gene Results\n\n\n* Precision = 0.808\n* Recall = 0.940\n* F1 = 0.869\n* Accuracy = 0.862\n* AUC = 0.... |
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. -->
# marker-associations-snp-binary-base
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["marker-associations-snp-binary-base"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "marker-associations-snp-binary-base", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset"... | jambo/marker-associations-snp-binary-base | null | [
"transformers",
"pytorch",
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"text-classification",
"generated_from_trainer",
"dataset:marker-associations-snp-binary-base",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-marker-associations-snp-binary-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us
| marker-associations-snp-binary-base
===================================
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the marker-associations-snp-binary-base dataset.
It achieves the following results on the evaluation set:
* Loss: 0.4027
* Precision: 0.9384
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 1\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 15",
"### Traini... | [
"TAGS\n#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-marker-associations-snp-binary-base #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* lea... |
text-classification | transformers |
# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-renet
A model for detecting gene disease associations from abstracts. The model classifies as 0 for no association, or 1 for some association.
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://... | {"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["renet"], "metrics": ["precision", "recall", "f1", "accuracy"], "model_index": [{"name": "BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-renet", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "datase... | jambo/microsoftBio-renet | null | [
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"bert",
"text-classification",
"generated_from_trainer",
"dataset:renet",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-renet #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-renet
A model for detecting gene disease associations from abstracts. The model classifies as 0 for no association, or 1 for some association.
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the REN... | [
"# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-renet\n\nA model for detecting gene disease associations from abstracts. The model classifies as 0 for no association, or 1 for some association.\n\nThis model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on... | [
"TAGS\n#transformers #pytorch #bert #text-classification #generated_from_trainer #dataset-renet #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-renet\n\nA model for detecting gene disease associations from abstracts. The mod... |
fill-mask | transformers |
# BERT base for Dhivehi
Pretrained model on Dhivehi language using masked language modeling (MLM).
## Tokenizer
The *WordPiece* tokenizer uses several components:
* **Normalization**: lowercase and then NFKD unicode normalization.
* **Pretokenization**: splits by whitespace and punctuation.
* **Postprocessing**: s... | {"language": ["dv"], "license": "apache-2.0"} | jamescalam/bert-base-dv | null | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"dv",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"dv"
] | TAGS
#transformers #pytorch #bert #fill-mask #dv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# BERT base for Dhivehi
Pretrained model on Dhivehi language using masked language modeling (MLM).
## Tokenizer
The *WordPiece* tokenizer uses several components:
* Normalization: lowercase and then NFKD unicode normalization.
* Pretokenization: splits by whitespace and punctuation.
* Postprocessing: single senten... | [
"# BERT base for Dhivehi\n\nPretrained model on Dhivehi language using masked language modeling (MLM).",
"## Tokenizer\n\nThe *WordPiece* tokenizer uses several components:\n\n* Normalization: lowercase and then NFKD unicode normalization.\n* Pretokenization: splits by whitespace and punctuation.\n* Postprocessin... | [
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"## Tokenizer\n\nThe *WordPiece* tokenizer uses several components:\n\n* Nor... |
sentence-similarity | sentence-transformers |
# Augmented SBERT STSb
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
It is used as a demo model within the [NLP for Semantic Search course](https://www.pinecone.io/le... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | jamescalam/bert-stsb-aug | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# Augmented SBERT STSb
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
It is used as a demo model within the NLP for Semantic Search course, for the chapter on In-domain Data Augmentation with ... | [
"# Augmented SBERT STSb\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.\n\nIt is used as a demo model within the NLP for Semantic Search course, for the chapter on In-domain Data Augmentati... | [
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"# Augmented SBERT STSb\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clusteri... |
sentence-similarity | sentence-transformers |
# Augmented SBERT STSb
This is a [sentence-transformers](https://www.SBERT.net) cross encoder model.
It is used as a demo model within the [NLP for Semantic Search course](https://www.pinecone.io/learn/nlp), for the chapter on [In-domain Data Augmentation with BERT](https://www.pinecone.io/learn/data-augmentation/).... | {"tags": ["sentence-transformers", "sentence-similarity", "transformers", "cross-encoder"], "pipeline_tag": "sentence-similarity"} | jamescalam/bert-stsb-cross-encoder | null | [
"sentence-transformers",
"pytorch",
"bert",
"text-classification",
"sentence-similarity",
"transformers",
"cross-encoder",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #bert #text-classification #sentence-similarity #transformers #cross-encoder #endpoints_compatible #region-us
|
# Augmented SBERT STSb
This is a sentence-transformers cross encoder model.
It is used as a demo model within the NLP for Semantic Search course, for the chapter on In-domain Data Augmentation with BERT.
| [
"# Augmented SBERT STSb\n\nThis is a sentence-transformers cross encoder model.\n\nIt is used as a demo model within the NLP for Semantic Search course, for the chapter on In-domain Data Augmentation with BERT."
] | [
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"# Augmented SBERT STSb\n\nThis is a sentence-transformers cross encoder model.\n\nIt is used as a demo model within the NLP for Semantic Search course, for the... |
sentence-similarity | sentence-transformers |
# Gold-only BERT STSb
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
It is used as a demo model within the [NLP for Semantic Search course](https://www.pinecone.io/lea... | {"tags": ["sentence-transformers", "feature-extraction", "sentence-similarity", "transformers"], "pipeline_tag": "sentence-similarity"} | jamescalam/bert-stsb-gold | null | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us
|
# Gold-only BERT STSb
This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
It is used as a demo model within the NLP for Semantic Search course, for the chapter on In-domain Data Augmentation with B... | [
"# Gold-only BERT STSb\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.\n\nIt is used as a demo model within the NLP for Semantic Search course, for the chapter on In-domain Data Augmentatio... | [
"TAGS\n#sentence-transformers #pytorch #bert #feature-extraction #sentence-similarity #transformers #endpoints_compatible #region-us \n",
"# Gold-only BERT STSb\n\nThis is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clusterin... |
text-generation | transformers |
# Spike DialoGPT Model | {"tags": ["conversational"]} | jamestop00/DialoGPT-spike-medium | 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
|
# Spike DialoGPT Model | [
"# Spike DialoGPT Model"
] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Spike DialoGPT Model"
] |
null | transformers |
# BERTSSON Models
The models are trained on:
- Government Text
- Swedish Literature
- Swedish News
Corpus size: Roughly 6B tokens.
The following models are currently available:
- **bertsson** - A BERT base model trained with the same hyperparameters as first published by Google.
All models are cased and trained w... | {"language": "sv"} | jannesg/bertsson | null | [
"transformers",
"pytorch",
"jax",
"bert",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"sv"
] | TAGS
#transformers #pytorch #jax #bert #sv #endpoints_compatible #region-us
|
# BERTSSON Models
The models are trained on:
- Government Text
- Swedish Literature
- Swedish News
Corpus size: Roughly 6B tokens.
The following models are currently available:
- bertsson - A BERT base model trained with the same hyperparameters as first published by Google.
All models are cased and trained with ... | [
"# BERTSSON Models\n\nThe models are trained on:\n- Government Text\n- Swedish Literature\n- Swedish News\n\nCorpus size: Roughly 6B tokens.\n\nThe following models are currently available:\n\n- bertsson - A BERT base model trained with the same hyperparameters as first published by Google.\n\nAll models are cased ... | [
"TAGS\n#transformers #pytorch #jax #bert #sv #endpoints_compatible #region-us \n",
"# BERTSSON Models\n\nThe models are trained on:\n- Government Text\n- Swedish Literature\n- Swedish News\n\nCorpus size: Roughly 6B tokens.\n\nThe following models are currently available:\n\n- bertsson - A BERT base model trained... |
fill-mask | transformers |
# Takalani Sesame - Salie - Afrikaans 🇿🇦
<img src="https://pbs.twimg.com/media/EVjR6BsWoAAFaq5.jpg" width="600"/>
## Model description
Takalani Sesame (named after the South African version of Sesame Street) is a project that aims to promote the use of South African languages in NLP, and in particular look at te... | {"language": ["af"], "license": "mit", "tags": ["af", "fill-mask", "pytorch", "roberta", "masked-lm"], "thumbnail": "https://pbs.twimg.com/media/EVjR6BsWoAAFaq5.jpg"} | jannesg/takalane_afr_roberta | null | [
"transformers",
"pytorch",
"jax",
"roberta",
"fill-mask",
"af",
"masked-lm",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"af"
] | TAGS
#transformers #pytorch #jax #roberta #fill-mask #af #masked-lm #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Takalani Sesame - Salie - Afrikaans 🇿🇦
<img src="URL width="600"/>
## Model description
Takalani Sesame (named after the South African version of Sesame Street) is a project that aims to promote the use of South African languages in NLP, and in particular look at techniques for low-resource languages to equali... | [
"# Takalani Sesame - Salie - Afrikaans 🇿🇦\n\n<img src=\"URL width=\"600\"/>",
"## Model description\n\nTakalani Sesame (named after the South African version of Sesame Street) is a project that aims to promote the use of South African languages in NLP, and in particular look at techniques for low-resource langu... | [
"TAGS\n#transformers #pytorch #jax #roberta #fill-mask #af #masked-lm #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Takalani Sesame - Salie - Afrikaans 🇿🇦\n\n<img src=\"URL width=\"600\"/>",
"## Model description\n\nTakalani Sesame (named after the South African version of Sesame... |
fill-mask | transformers |
# Takalani Sesame - Ndebele 🇿🇦
<img src="https://pbs.twimg.com/media/EVjR6BsWoAAFaq5.jpg" width="600"/>
## Model description
Takalani Sesame (named after the South African version of Sesame Street) is a project that aims to promote the use of South African languages in NLP, and in particular look at techniques f... | {"language": ["nr"], "license": "mit", "tags": ["nr", "fill-mask", "pytorch", "roberta", "masked-lm"], "thumbnail": "https://pbs.twimg.com/media/EVjR6BsWoAAFaq5.jpg"} | jannesg/takalane_nbl_roberta | null | [
"transformers",
"pytorch",
"jax",
"roberta",
"fill-mask",
"nr",
"masked-lm",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"nr"
] | TAGS
#transformers #pytorch #jax #roberta #fill-mask #nr #masked-lm #license-mit #autotrain_compatible #endpoints_compatible #region-us
|
# Takalani Sesame - Ndebele 🇿🇦
<img src="URL width="600"/>
## Model description
Takalani Sesame (named after the South African version of Sesame Street) is a project that aims to promote the use of South African languages in NLP, and in particular look at techniques for low-resource languages to equalise perform... | [
"# Takalani Sesame - Ndebele 🇿🇦\n\n<img src=\"URL width=\"600\"/>",
"## Model description\n\nTakalani Sesame (named after the South African version of Sesame Street) is a project that aims to promote the use of South African languages in NLP, and in particular look at techniques for low-resource languages to eq... | [
"TAGS\n#transformers #pytorch #jax #roberta #fill-mask #nr #masked-lm #license-mit #autotrain_compatible #endpoints_compatible #region-us \n",
"# Takalani Sesame - Ndebele 🇿🇦\n\n<img src=\"URL width=\"600\"/>",
"## Model description\n\nTakalani Sesame (named after the South African version of Sesame Street) i... |
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