modelId stringlengths 4 112 | sha stringlengths 40 40 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringclasses 29
values | private bool 1
class | author stringlengths 2 38 ⌀ | config null | id stringlengths 4 112 | downloads float64 0 36.8M ⌀ | likes float64 0 712 ⌀ | library_name stringclasses 17
values | __index_level_0__ int64 0 38.5k | readme stringlengths 0 186k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
unicamp-dl/ptt5-large-portuguese-vocab | 6de512d9b277921a6f6d8f009752e1fb0059db56 | 2021-03-24T22:17:55.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"pt",
"dataset:brWaC",
"transformers",
"tensorflow",
"pt-br",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | unicamp-dl | null | unicamp-dl/ptt5-large-portuguese-vocab | 107 | 1 | transformers | 4,500 | ---
language: pt
license: mit
tags:
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- brWaC
widget:
- text: "Texto de exemplo em português"
inference: false
---
# Portuguese T5 (aka "PTT5")
## Introduction
PTT5 is a T5 model pretrained in the BrWac corpus, a large collection of web pages in Portuguese, improvi... |
Shitao/msmarco_query_encoder | 0179561052faa00dcbd0e944350ea5f7552930f4 | 2022-04-24T17:01:57.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | Shitao | null | Shitao/msmarco_query_encoder | 107 | null | transformers | 4,501 | ---
license: apache-2.0
---
|
doc2query/msmarco-german-mt5-base-v1 | f0e1c137c34a80d3327b8349eb43b5df30bd9028 | 2022-04-29T09:03:18.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"de",
"dataset:unicamp-dl/mmarco",
"arxiv:1904.08375",
"arxiv:2104.08663",
"arxiv:2112.07577",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | doc2query | null | doc2query/msmarco-german-mt5-base-v1 | 107 | 1 | transformers | 4,502 | ---
language: de
datasets:
- unicamp-dl/mmarco
widget:
- text: "Python ist eine universelle, üblicherweise interpretierte, höhere Programmiersprache. Sie hat den Anspruch, einen gut lesbaren, knappen Programmierstil zu fördern. So werden beispielsweise Blöcke nicht durch geschweifte Klammern, sondern durch Einrück... |
Ahmed9275/Vit-Cifar100 | 33677f4f54c5cf3b0057dd374e6de24dafdd67df | 2022-05-19T01:26:45.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:cifar100",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | Ahmed9275 | null | Ahmed9275/Vit-Cifar100 | 107 | 1 | transformers | 4,503 | ---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- cifar100
metrics:
- accuracy
model-index:
- name: vit-base-beans-demo-v5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: Cifar100
type: cifar100
args: cif... |
inkoziev/rugpt_interpreter | cce0af88fa2bf3292a8cc057a088a824a3e04ce2 | 2022-06-19T12:02:48.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"transformers",
"Text generation",
"license:unlicense"
] | text-generation | false | inkoziev | null | inkoziev/rugpt_interpreter | 107 | 3 | transformers | 4,504 | ---
tags: Text generation
license: unlicense
language: ru
widget:
- text: "- Как тебя зовут? - Джульетта Мао #"
- text: "- А живешь где? - В поясе астероидов #"
---
## Задача Incomplete Utterance Restoration
Генеративная модель на основе [sberbank-ai/rugpt3large_based_on_gpt2](https://huggingface.co/sberbank-ai... |
keithhon/paraphrase-multilingual-MiniLM-L12-v2 | 95e9642a135281d46946a5fb542732eadfe218ac | 2022-07-25T06:50:16.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"multilingual",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | keithhon | null | keithhon/paraphrase-multilingual-MiniLM-L12-v2 | 107 | null | sentence-transformers | 4,505 | ---
pipeline_tag: sentence-similarity
language: multilingual
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences &... |
GroNLP/gpt2-small-italian-embeddings | 471966c990fe69c6eb1d776791bf5aa89ac31f77 | 2021-05-21T09:57:57.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"it",
"arxiv:2012.05628",
"transformers",
"adaption",
"recycled",
"gpt2-small"
] | text-generation | false | GroNLP | null | GroNLP/gpt2-small-italian-embeddings | 106 | null | transformers | 4,506 | ---
language: it
tags:
- adaption
- recycled
- gpt2-small
pipeline_tag: text-generation
---
# GPT-2 recycled for Italian (small, adapted lexical embeddings)
[Wietse de Vries](https://www.semanticscholar.org/author/Wietse-de-Vries/144611157) •
[Malvina Nissim](https://www.semanticscholar.org/author/M.-Nissim/2742475)
... |
MoritzLaurer/MiniLM-L6-mnli-fever-docnli-ling-2c | 378b6a5483d6a3eaedd08a41b11cc61e7ec11896 | 2021-12-22T18:36:19.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"arxiv:2104.07179",
"arxiv:2106.09449",
"transformers",
"zero-shot-classification"
] | text-classification | false | MoritzLaurer | null | MoritzLaurer/MiniLM-L6-mnli-fever-docnli-ling-2c | 106 | null | transformers | 4,507 | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
metrics:
- accuracy
widget:
- text: "I first thought that I liked the movie, but upon second thought the movie was actually disappointing. [SEP] The movie was good."
---
# MiniLM-L6-mnli-fever-docnli-ling-2c
## Model description
This model was ... |
dbmdz/convbert-base-german-europeana-cased | f01a50fead9205fa24189c41bfbc7c4a2d299881 | 2021-02-06T20:38:13.000Z | [
"pytorch",
"tf",
"convbert",
"feature-extraction",
"de",
"transformers",
"historic german",
"license:mit"
] | feature-extraction | false | dbmdz | null | dbmdz/convbert-base-german-europeana-cased | 106 | 1 | transformers | 4,508 | ---
language: de
license: mit
tags:
- "historic german"
---
# 🤗 + 📚 dbmdz ConvBERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana ConvBERT model 🎉
# German Europeana ConvBERT
We use the open source [Europeana newspapers](http://www.eu... |
meedan/indian-sbert | df5f9a82da83c8ff832ba17dc6b7979206d6feed | 2021-02-22T22:37:11.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | meedan | null | meedan/indian-sbert | 106 | null | transformers | 4,509 | Entry not found |
phiyodr/roberta-large-finetuned-squad2 | 958e58c18ed6c9ed583bcab0b9bc72d67a08430c | 2021-05-20T19:27:52.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"en",
"dataset:squad2",
"arxiv:1907.11692",
"arxiv:1806.03822",
"transformers",
"autotrain_compatible"
] | question-answering | false | phiyodr | null | phiyodr/roberta-large-finetuned-squad2 | 106 | null | transformers | 4,510 | ---
language: en
tags:
- pytorch
- question-answering
datasets:
- squad2
metrics:
- exact
- f1
widget:
- text: "What discipline did Winkelmann create?"
context: "Johann Joachim Winckelmann was a German art historian and archaeologist. He was a pioneering Hellenist who first articulated the difference between Greek, G... |
projecte-aina/bart-base-ca-casum | 09bc6142129b80f3ea2b7e5e38a9976e2b41eaff | 2022-07-25T06:48:05.000Z | [
"pytorch",
"bart",
"text2text-generation",
"ca",
"dataset:projecte-aina/casum",
"arxiv:2202.06871",
"transformers",
"summarization",
"license:mit",
"autotrain_compatible"
] | summarization | false | projecte-aina | null | projecte-aina/bart-base-ca-casum | 106 | null | transformers | 4,511 | ---
language: "ca"
license: mit
tags:
- summarization
widget:
- text: "El projecte AINA generarà els recursos digitals i lingüístics necessaris per facilitar el desenvolupament d’aplicacions basades en la intel·ligència artificial i les tecnologies de la llengua, com ara els assistents de veu, els traductors automàtics... |
superb/hubert-base-superb-sid | fd0c9962f8a01e274b9a7996e007775293d1d77e | 2021-11-04T16:03:27.000Z | [
"pytorch",
"hubert",
"audio-classification",
"en",
"dataset:superb",
"arxiv:2105.01051",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | audio-classification | false | superb | null | superb/hubert-base-superb-sid | 106 | null | transformers | 4,512 | ---
language: en
datasets:
- superb
tags:
- speech
- audio
- hubert
- audio-classification
widget:
- example_title: VoxCeleb Speaker id10003
src: https://cdn-media.huggingface.co/speech_samples/VoxCeleb1_00003.wav
- example_title: VoxCeleb Speaker id10004
src: https://cdn-media.huggingface.co/speech_samples/VoxCele... |
zhiheng-huang/bert-base-uncased-embedding-relative-key | 62d01e1af97f972b2954e691466d84442f3d3659 | 2021-05-20T09:46:58.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | zhiheng-huang | null | zhiheng-huang/bert-base-uncased-embedding-relative-key | 106 | null | transformers | 4,513 | Entry not found |
doc2query/msmarco-japanese-mt5-base-v1 | 5effea381731300f68a617eec753d82e34f2c096 | 2022-04-29T12:05:37.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"ja",
"dataset:unicamp-dl/mmarco",
"arxiv:1904.08375",
"arxiv:2104.08663",
"arxiv:2112.07577",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | doc2query | null | doc2query/msmarco-japanese-mt5-base-v1 | 106 | null | transformers | 4,514 | ---
language: ja
datasets:
- unicamp-dl/mmarco
widget:
- text: "Python（パイソン）はインタープリタ型の高水準汎用プログラミング言語である。グイド・ヴァン・ロッサムにより創り出され、1991年に最初にリリースされたPythonの設計哲学は、有意なホワイトスペース(オフサイドルール)の顕著な使用によってコードの可読性を重視している。その言語構成とオブジェクト指向のアプローチは、プログラマが小規模なプロジェクトから大規模なプロジェクトまで、明確で論理的なコードを書くのを支援することを目的としている。"
license: apache-2.0
---
... |
autoevaluate/binary-classification | 5d6b168b009889a2eedbc858ecd212de4a7412c7 | 2022-06-21T13:42:46.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | autoevaluate | null | autoevaluate/binary-classification | 106 | 1 | transformers | 4,515 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: autoevaluate-binary-classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- name... |
domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt | 3031f6d592d10a2c0d9ce8cad5cffa00202762d7 | 2022-06-30T19:24:19.000Z | [
"pytorch",
"tensorboard",
"deberta-v2",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | fill-mask | false | domenicrosati | null | domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt | 106 | null | transformers | 4,516 | ---
license: mit
tags:
- fill-mask
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large-dapt-scientific-papers-pubmed-tapt
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... |
freedomking/mc-bert | d057742eb21845be851d9b434653e76edbefcb62 | 2022-07-15T10:14:00.000Z | [
"pytorch",
"transformers"
] | null | false | freedomking | null | freedomking/mc-bert | 106 | null | transformers | 4,517 | MC-BERT is a novel conceptualized representation learning approach for the medical domain. First, we use a different mask generation procedure to mask spans of tokens, rather than only random ones. We also introduce two kinds of masking strategies, namely whole entity masking and whole span masking. Finally, MC-BERT sp... |
naver-clova-ix/donut-base-finetuned-cord-v1 | 49cf2da80d46da3bc8fa41eff7631848d6d59705 | 2022-07-20T06:01:09.000Z | [
"pytorch",
"donut",
"transformers",
"license:mit"
] | null | false | naver-clova-ix | null | naver-clova-ix/donut-base-finetuned-cord-v1 | 106 | null | transformers | 4,518 | ---
license: mit
---
|
bloom-testing/test-bloomd-350m-generation-inference | c062d86b2739726a4249df07e58f200aa292b613 | 2022-07-27T06:03:47.000Z | [
"pytorch",
"bloom",
"feature-extraction",
"transformers"
] | feature-extraction | false | bloom-testing | null | bloom-testing/test-bloomd-350m-generation-inference | 106 | null | transformers | 4,519 | Entry not found |
Cedille/fr-boris | cb981d4d03b87647b25b7627868bde76420719f9 | 2022-03-15T08:36:54.000Z | [
"pytorch",
"gptj",
"text-generation",
"fr",
"dataset:c4",
"arxiv:2202.03371",
"transformers",
"causal-lm",
"license:mit"
] | text-generation | false | Cedille | null | Cedille/fr-boris | 105 | 21 | transformers | 4,520 | ---
language: fr
license: mit
tags:
- pytorch
- causal-lm
datasets:
- c4
---
# Cedille AI
Cedille is a project to bring large language models to non-English languages.
## fr-boris
Boris is a 6B parameter autoregressive language model based on the GPT-J architecture and trained using the [mesh-transformer-jax](https:/... |
Helsinki-NLP/opus-mt-id-fr | 308322e870f05e563cb9897ffa664937ecd8de24 | 2021-09-09T22:11:22.000Z | [
"pytorch",
"marian",
"text2text-generation",
"id",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-id-fr | 105 | null | transformers | 4,521 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-id-fr
* source languages: id
* target languages: fr
* OPUS readme: [id-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/id-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
crabz/FERNET-CC_sk-ner | 713e1e0d030d4c903b070e5ec7116afb2c72b511 | 2021-12-10T18:46:02.000Z | [
"pytorch",
"bert",
"token-classification",
"sk",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | crabz | null | crabz/FERNET-CC_sk-ner | 105 | null | transformers | 4,522 | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
language:
- sk
inference: false
model-index:
- name: fernet-sk-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann sk
... |
dobbytk/letr-sol-profanity-filter | b020c49bd3c85d0e8d361fe7bd1e78513bf59fed | 2021-10-20T14:11:37.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | dobbytk | null | dobbytk/letr-sol-profanity-filter | 105 | null | transformers | 4,523 | Entry not found |
microsoft/unispeech-sat-base-plus-sd | 5aba16d1c7a91748fd0f08d26d57587a426aa765 | 2021-12-17T18:40:56.000Z | [
"pytorch",
"unispeech-sat",
"audio-frame-classification",
"en",
"arxiv:1912.07875",
"arxiv:2106.06909",
"arxiv:2101.00390",
"arxiv:2110.05752",
"transformers",
"speech"
] | null | false | microsoft | null | microsoft/unispeech-sat-base-plus-sd | 105 | null | transformers | 4,524 | ---
language:
- en
tags:
- speech
---
# UniSpeech-SAT-Base for Speaker Diarization
[Microsoft's UniSpeech](https://www.microsoft.com/en-us/research/publication/unispeech-unified-speech-representation-learning-with-labeled-and-unlabeled-data/)
The model was pretrained on 16kHz sampled speech audio with utterance and ... |
Lvxue/finetuned-mt5-base-10epoch | abe81083a36f148167359d5f351339e217fafc87 | 2022-07-14T12:21:17.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"en",
"ro",
"dataset:wmt16",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Lvxue | null | Lvxue/finetuned-mt5-base-10epoch | 105 | null | transformers | 4,525 | ---
language:
- en
- ro
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
model-index:
- name: finetuned-mt5-base-10epoch
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... |
google/ncsnpp-church-256 | 819e60b10ad98bfeac12931806cca04645aa5699 | 2022-07-21T14:39:07.000Z | [
"diffusers",
"arxiv:2011.13456",
"pytorch",
"unconditional-image-generation",
"license:apache-2.0"
] | unconditional-image-generation | false | google | null | google/ncsnpp-church-256 | 105 | null | diffusers | 4,526 | ---
license: apache-2.0
tags:
- pytorch
- diffusers
- unconditional-image-generation
---
# Score-Based Generative Modeling through Stochastic Differential Equations (SDE)
**Paper**: [Score-Based Generative Modeling through Stochastic Differential Equations](https://arxiv.org/abs/2011.13456)
**Authors**: Yang Song, J... |
HScomcom/gpt2-lovecraft | 1b2a25b2ffe28cf5dfb4e3b166ebee53c0a189ab | 2021-05-21T10:38:11.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | HScomcom | null | HScomcom/gpt2-lovecraft | 104 | 2 | transformers | 4,527 | ### Model information
Fine tuning data: https://www.kaggle.com/bennijesus/lovecraft-fiction
License: CC0: Public Domain
Base model: gpt-2 large
Epoch: 30
Train runtime: 10307.3488 secs
Loss: 0.0292
API page: [Ainize](https://ainize.ai/fpem123/GPT2-LoveCraft?branch=master)
Demo page: [End-poi... |
Helsinki-NLP/opus-mt-iir-en | aa50367843cc845ac9310c7f771e1b302eaa5fcd | 2020-08-21T14:42:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bn",
"or",
"gu",
"mr",
"ur",
"hi",
"ps",
"os",
"as",
"si",
"iir",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-iir-en | 104 | null | transformers | 4,528 | ---
language:
- bn
- or
- gu
- mr
- ur
- hi
- ps
- os
- as
- si
- iir
- en
tags:
- translation
license: apache-2.0
---
### iir-eng
* source group: Indo-Iranian languages
* target group: English
* OPUS readme: [iir-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/iir-eng/README.md)
* m... |
Helsinki-NLP/opus-mt-ja-es | 2631f1ca099e100f0cccf9dad5dc60d67a146775 | 2021-09-10T13:53:16.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-es | 104 | null | transformers | 4,529 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ja-es
* source languages: ja
* target languages: es
* OPUS readme: [ja-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ja-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-lt-fr | 0f3bdc8413bb89716e09c90ecb599b0908aea188 | 2021-09-10T13:55:37.000Z | [
"pytorch",
"marian",
"text2text-generation",
"lt",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-lt-fr | 104 | null | transformers | 4,530 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-lt-fr
* source languages: lt
* target languages: fr
* OPUS readme: [lt-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/lt-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
NovelAI/genji-python-6B | d7eb36c822b24cd9d8fa47087f4e2751841c1a75 | 2021-08-06T19:15:41.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"en",
"dataset:the Pile",
"arxiv:2104.09864",
"transformers",
"causal-lm",
"license:apache-2.0"
] | text-generation | false | NovelAI | null | NovelAI/genji-python-6B | 104 | 24 | transformers | 4,531 | ---
language:
- en
tags:
- pytorch
- causal-lm
license: apache-2.0
datasets:
- the Pile
---
# Genji-python 6B
For example usage or to easily use the model you can check our colab notebook:
[Notebook](https://colab.research.google.com/drive/1PnWpx02IEUkY8jhLKd_NewUGEXahAska?usp=sharing)
## Model Description
Genji is... |
huawei-noah/TinyBERT_4L_zh | 152bf15d86715b41dd89c1e03cf5664963d9b005 | 2020-10-14T09:03:53.000Z | [
"pytorch",
"transformers"
] | null | false | huawei-noah | null | huawei-noah/TinyBERT_4L_zh | 104 | 3 | transformers | 4,532 | Entry not found |
facebook/flava-image-codebook | 4285ec53336ae34be9337b41d79cee9fc92b7a71 | 2022-05-08T22:06:47.000Z | [
"pytorch",
"flava_image_codebook",
"transformers",
"license:bsd-3-clause"
] | null | false | facebook | null | facebook/flava-image-codebook | 104 | null | transformers | 4,533 | ---
license: bsd-3-clause
---
|
kabelomalapane/en_nso_ukuxhumana_model | e90db4e63605d6ad0e901acf715a0a45e9018065 | 2022-05-21T01:17:17.000Z | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | kabelomalapane | null | kabelomalapane/en_nso_ukuxhumana_model | 104 | null | transformers | 4,534 | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: en_nso_ukuxhumana_model
results: []
---
<!-- 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 th... |
armandnlp/gpt2-TOD_finetuned_SGD | 7201380584b08858dfc7ebd80618f4873894a30c | 2022-07-15T13:57:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | armandnlp | null | armandnlp/gpt2-TOD_finetuned_SGD | 104 | 0 | transformers | 4,535 | ---
pipeline_tag: text-generation
widget:
- text: "<|context|> <|user|> I want to go to the restaurant tomorrow at 2 pm.<|endofcontext|>"
- text: "<|context|> <|user|> I want to go to the restaurant.<|system|> What food would you like to eat ? <|user|> Italian sounds good. <|endofcontext|>"
--- |
rajpurkarlab/biobert-finetuned-prior-rmv | 75526b5c532870f1069c6aafd668704e8f838d30 | 2022-07-19T21:08:13.000Z | [
"pytorch",
"bert",
"token-classification",
"py",
"transformers",
"autotrain_compatible"
] | token-classification | false | rajpurkarlab | null | rajpurkarlab/biobert-finetuned-prior-rmv | 104 | 1 | transformers | 4,536 | ---
language:
- py
metrics:
- f1
---
To use our fine-tuned BioBERT model to remove references to priors from radiology reports, run the following:
```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
modelname = "rajpurkarlab/biobert-finetuned-prior-rmv"
tokenizer = AutoTokenizer.fr... |
Lurunchik/nf-cats | 32b89caba4842c66eec6e9ea0a5b16426781f9ee | 2022-07-18T14:16:02.000Z | [
"pytorch",
"roberta",
"en",
"transformers",
"text-classification",
"license:mit"
] | text-classification | false | Lurunchik | null | Lurunchik/nf-cats | 104 | null | transformers | 4,537 | ---
language:
- en
license: mit
tags:
- text-classification
inference: false
widget:
- text: "Why do we need an NFQA taxonomy?"
---
# Non Factoid Question Category classification in English
## NFQA model
Repository: [https://github.com/Lurunchik/NF-CATS](https://github.com/Lurunchik/NF-CATS)
Model trained wi... |
microsoft/codereviewer | bd0e81b54df3cbc7c7a2364a231f700d84de1f34 | 2022-07-25T06:37:04.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | microsoft | null | microsoft/codereviewer | 104 | 1 | transformers | 4,538 | ---
license: apache-2.0
---
|
Geotrend/distilbert-base-en-fr-cased | c4df3153dd3046d8de953c2e0bd09f784c2b3e01 | 2021-08-16T13:46:47.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"multilingual",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/distilbert-base-en-fr-cased | 103 | null | transformers | 4,539 | ---
language: multilingual
datasets: wikipedia
license: apache-2.0
---
# distilbert-base-en-fr-cased
We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.
Our versions give exactly the same repres... |
Helsinki-NLP/opus-mt-ja-vi | 84f687d22ffc2a3a79894ff0e8404d71ccf02e18 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-vi | 103 | null | transformers | 4,540 | ---
language:
- ja
- vi
tags:
- translation
license: apache-2.0
---
### jpn-vie
* source group: Japanese
* target group: Vietnamese
* OPUS readme: [jpn-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-vie/README.md)
* model: transformer-align
* source language(s): jpn jpn_Bopo jpn... |
Helsinki-NLP/opus-mt-tn-en | a2a7709c904b9a76939d9512117e3081d7d2bd5a | 2021-09-11T10:48:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"tn",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tn-en | 103 | null | transformers | 4,541 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-tn-en
* source languages: tn
* target languages: en
* OPUS readme: [tn-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/tn-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-trk-en | b9c8cdb8d74d103713f3195d830dec06dc6798bf | 2020-08-21T14:42:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"tt",
"cv",
"tk",
"tr",
"ba",
"trk",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-trk-en | 103 | 1 | transformers | 4,542 | ---
language:
- tt
- cv
- tk
- tr
- ba
- trk
- en
tags:
- translation
license: apache-2.0
---
### trk-eng
* source group: Turkic languages
* target group: English
* OPUS readme: [trk-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/trk-eng/README.md)
* model: transformer
* source lang... |
ahmetbagci/bert2bert-turkish-paraphrase-generation | 27c023c0e5bdcf1067c38093c88411c488e4e382 | 2021-10-18T10:17:40.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"tr",
"transformers",
"paraphrasing",
"seq2seq",
"bert",
"autotrain_compatible"
] | text2text-generation | false | ahmetbagci | null | ahmetbagci/bert2bert-turkish-paraphrase-generation | 103 | 4 | transformers | 4,543 | ---
language:
- tr
tags:
- paraphrasing
- encoder-decoder
- seq2seq
- bert
---
#Bert2Bert Turkish Paraphrase Generation
#INISTA 2021
#Comparison of Turkish Paraphrase Generation Models
#Dataset
The dataset used in model training was created with the combination of the translation of the QQP dataset and manually g... |
avichr/hebEMO_surprise | e9f771cd3ef5d3231157b175597d3a34f5aeccb1 | 2022-04-15T09:36:33.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | avichr | null | avichr/hebEMO_surprise | 103 | null | transformers | 4,544 | # HebEMO - Emotion Recognition Model for Modern Hebrew
<img align="right" src="https://github.com/avichaychriqui/HeBERT/blob/main/data/heBERT_logo.png?raw=true" width="250">
HebEMO is a tool that detects polarity and extracts emotions from modern Hebrew User-Generated Content (UGC), which was trained on a unique Covid... |
bhadresh-savani/albert-base-v2-emotion | 4812613b3c07c549e13f09bb266dbf0e59f48de7 | 2021-09-15T18:03:36.000Z | [
"pytorch",
"tf",
"jax",
"albert",
"text-classification",
"en",
"dataset:emotion",
"arxiv:1909.11942",
"transformers",
"emotion",
"license:apache-2.0"
] | text-classification | false | bhadresh-savani | null | bhadresh-savani/albert-base-v2-emotion | 103 | null | transformers | 4,545 | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- emotion
- pytorch
license: apache-2.0
datasets:
- emotion
metrics:
- Accuracy, F1 Score
---
# Albert-base-v2-emotion
## Model description:
[Albert](https:/... |
comodoro/wav2vec2-xls-r-300m-west-slavic-cv8 | 4298ddc44143969a783c2d8d72c7de19ae57597d | 2022-03-23T18:27:31.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"cs",
"hsb",
"pl",
"sk",
"sl",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"xlsr-fine-tuning-week",
"l... | automatic-speech-recognition | false | comodoro | null | comodoro/wav2vec2-xls-r-300m-west-slavic-cv8 | 103 | null | transformers | 4,546 | ---
language:
- cs
- hsb
- pl
- sk
- sl
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
- xlsr-fine-tuning-week
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-xls-r-300m-west... |
facebook/wav2vec2-xls-r-2b | 12a34a57dc2d6fa6050b45d848b457dec663de2e | 2021-11-18T16:32:44.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"multilingual",
"dataset:common_voice",
"dataset:multilingual_librispeech",
"arxiv:2111.09296",
"transformers",
"speech",
"xls_r",
"xls_r_pretrained",
"license:apache-2.0"
] | null | false | facebook | null | facebook/wav2vec2-xls-r-2b | 103 | 11 | transformers | 4,547 | ---
language: multilingual
datasets:
- common_voice
- multilingual_librispeech
tags:
- speech
- xls_r
- xls_r_pretrained
license: apache-2.0
---
# Wav2Vec2-XLS-R-2B
[Facebook's Wav2Vec2 XLS-R](https://ai.facebook.com/blog/xls-r-self-supervised-speech-processing-for-128-languages) counting **2 billion** parameters.
!... |
google/bert_uncased_L-10_H-128_A-2 | 0c5790f28634a0a84d66543cd3f6967264248f54 | 2021-05-19T17:23:15.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-10_H-128_A-2 | 103 | null | transformers | 4,548 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
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 Word... |
google/t5-efficient-xxl | 8f1f4fbd645dacf613cadf2336afc7a6b142a8ec | 2022-02-15T10:57:22.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2109.10686",
"transformers",
"deep-narrow",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-efficient-xxl | 103 | 1 | transformers | 4,549 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-XXL (Deep-Narrow version)
T5-Efficient-XXL is a variation of [Google's original T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) following the [T5 model architecture](https://h... |
razent/SciFive-large-Pubmed | 12d03536796368152417dd4702d4eb32265d14a1 | 2022-03-20T17:46:20.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:pubmed",
"arxiv:2106.03598",
"transformers",
"token-classification",
"text-classification",
"question-answering",
"text-generation",
"autotrain_compatible"
] | text-classification | false | razent | null | razent/SciFive-large-Pubmed | 103 | null | transformers | 4,550 | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
---
# SciFive Pubmed Large
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs/2106.03598)
Autho... |
seyonec/ChemBERTa-zinc250k-v1 | 9caca1b46a6a3155b4b0ed3bd0772065b989ed3a | 2021-05-20T20:56:13.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | seyonec | null | seyonec/ChemBERTa-zinc250k-v1 | 103 | null | transformers | 4,551 | Entry not found |
voidful/albert_chinese_large | 00c124d3f4e027c43743139fa2dafa3783148eaa | 2021-08-03T05:06:31.000Z | [
"pytorch",
"albert",
"fill-mask",
"zh",
"transformers",
"autotrain_compatible"
] | fill-mask | false | voidful | null | voidful/albert_chinese_large | 103 | 2 | transformers | 4,552 | ---
language: zh
pipeline_tag: fill-mask
widget:
- text: "今天[MASK]情很好"
---
# albert_chinese_large
This a albert_chinese_large model from [Google's github](https://github.com/google-research/ALBERT)
converted by huggingface's [script](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_a... |
malmarjeh/bert2bert | d1c3f06198b726a04c74f7eb4a27077d387844a4 | 2022-06-29T14:14:02.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"ar",
"transformers",
"AraBERT",
"BERT",
"BERT2BERT",
"MSA",
"Arabic Text Summarization",
"Arabic News Title Generation",
"Arabic Paraphrasing",
"autotrain_compatible"
] | text2text-generation | false | malmarjeh | null | malmarjeh/bert2bert | 103 | null | transformers | 4,553 | ---
language:
- ar
tags:
- AraBERT
- BERT
- BERT2BERT
- MSA
- Arabic Text Summarization
- Arabic News Title Generation
- Arabic Paraphrasing
widget:
- text: "شهدت مدينة طرابلس، مساء أمس الأربعاء، احتجاجات شعبية وأعمال شغب لليوم الثالث على التوالي، وذلك بسبب تردي الوضع المعيشي والاقتصادي. واندلعت مواجه... |
agdsga/chinese-roberta-wwm-ext-large-finetuned-ner | d7ab9f4e8c800cf9b526116a35f346c5c3f7c0e9 | 2022-03-24T15:05:57.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | agdsga | null | agdsga/chinese-roberta-wwm-ext-large-finetuned-ner | 103 | null | transformers | 4,554 | Entry not found |
IIC/dpr-spanish-passage_encoder-allqa-base | b3ef76d4bc5190d96cbad2aae4b18cc290cd76b1 | 2022-04-02T15:05:07.000Z | [
"pytorch",
"bert",
"fill-mask",
"es",
"dataset:squad_es",
"dataset:PlanTL-GOB-ES/SQAC",
"dataset:IIC/bioasq22_es",
"arxiv:2004.04906",
"transformers",
"sentence similarity",
"passage retrieval",
"model-index",
"autotrain_compatible"
] | fill-mask | false | IIC | null | IIC/dpr-spanish-passage_encoder-allqa-base | 103 | 1 | transformers | 4,555 | ---
language:
- es
tags:
- sentence similarity # Example: audio
- passage retrieval # Example: automatic-speech-recognition
datasets:
- squad_es
- PlanTL-GOB-ES/SQAC
- IIC/bioasq22_es
metrics:
- eval_loss: 0.010779764448327261
- eval_accuracy: 0.9982682224158297
- eval_f1: 0.9446059155411182
- average_rank: 0.117285... |
Davlan/afro-xlmr-large | 9c59ab30d8d349e9ce36df8b98c2161287e29dc8 | 2022-05-29T12:37:24.000Z | [
"pytorch",
"xlm-roberta",
"fill-mask",
"arxiv:2204.06487",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | fill-mask | false | Davlan | null | Davlan/afro-xlmr-large | 103 | 1 | transformers | 4,556 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: afro-xlmr-large
results: []
---
# afro-xlmr-large
AfroXLMR-large was created by MLM adaptation of XLM-R-large model on 17 African languages (Afrikaans, Amharic, Hausa, Igbo, Malagasy, Chichewa, Oromo, Naija, Kinyarwanda, Kirundi, Shona, Somali, S... |
Narsil/bart-large-mnli-opti | 7a6d021721124565837dc508b48ff299adfcbebb | 2022-05-27T16:08:13.000Z | [
"pytorch",
"bart",
"text-classification",
"dataset:multi_nli",
"arxiv:1910.13461",
"arxiv:1909.00161",
"transformers",
"license:mit",
"zero-shot-classification"
] | zero-shot-classification | false | Narsil | null | Narsil/bart-large-mnli-opti | 103 | null | transformers | 4,557 | ---
license: mit
thumbnail: https://huggingface.co/front/thumbnails/facebook.png
pipeline_tag: zero-shot-classification
datasets:
- multi_nli
---
# bart-large-mnli
This is the checkpoint for [bart-large](https://huggingface.co/facebook/bart-large) after being trained on the [MultiNLI (MNLI)](https://huggingface.co/da... |
juliensimon/distilbert-amazon-shoe-reviews | e11edc9f0634152e952241aa61be10fd8b5ffd79 | 2022-06-29T14:48:10.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | juliensimon | null | juliensimon/distilbert-amazon-shoe-reviews | 103 | null | transformers | 4,558 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-amazon-shoe-reviews
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... |
erikycd/chatbot_hadita | 97c4ca4463f8e0c4119984354478c5a54dd1bad1 | 2022-07-01T00:08:55.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:wikipedia",
"transformers",
"conversational",
"license:gpl-3.0"
] | conversational | false | erikycd | null | erikycd/chatbot_hadita | 103 | null | transformers | 4,559 | ---
license: gpl-3.0
tags:
- conversational
- gpt2
language:
- en
datasets:
- wikipedia
widget:
- text: "Where are you from?"
example_title: "Basic question 1"
---
# DialoGPT small base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective.
## Model description
BE... |
Geotrend/distilbert-base-ru-cased | 3ca787456bffca9af5a564ac0e866a50af931e6e | 2021-08-16T13:27:34.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"ru",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/distilbert-base-ru-cased | 102 | 1 | transformers | 4,560 | ---
language: ru
datasets: wikipedia
license: apache-2.0
---
# distilbert-base-ru-cased
We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.
Our versions give exactly the same representations pro... |
Sora4762/DialoGPT-small-naruto1.1 | a863e99e28a313417dc69164b8267039e7758a95 | 2022-01-21T18:04:34.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Sora4762 | null | Sora4762/DialoGPT-small-naruto1.1 | 102 | null | transformers | 4,561 | ---
tags:
- conversational
---
# Naruto DialoGPT Model1.1 |
google/realm-orqa-nq-reader | ce9401d15939699b680b46c916b0c1955e777dbe | 2022-01-05T18:28:40.000Z | [
"pytorch",
"realm",
"en",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/realm-orqa-nq-reader | 102 | 1 | transformers | 4,562 | ---
language: en
license: apache-2.0
---
# realm-orqa-nq-reader
## Model description
The REALM checkpoint finetuned with Natural Question(NQ) dataset, converted from the TF checkpoint provided by Google Language.
The original paper, code, and checkpoints can be found [here](https://github.com/google-rese... |
mrm8488/electricidad-base-generator | 7df1cf48badff8791aa66567e214bc4ff127096a | 2020-12-11T21:54:10.000Z | [
"pytorch",
"electra",
"fill-mask",
"es",
"transformers",
"autotrain_compatible"
] | fill-mask | false | mrm8488 | null | mrm8488/electricidad-base-generator | 102 | 2 | transformers | 4,563 | ---
language: es
thumbnail: https://i.imgur.com/uxAvBfh.png
widget:
- text: "Madrid es una ciudad muy [MASK] en España."
---
## ELECTRICIDAD: The Spanish Electra [Imgur](https://imgur.com/uxAvBfh)
**Electricidad-base-generator** (uncased) is a ```base``` Electra like model (generator in this case) trained on a + 20... |
sentence-transformers/multi-qa-distilbert-dot-v1 | 99c2d7a977fac1242833986785da4be605a58c88 | 2021-08-23T18:15:50.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"sentence-transformers",
"feature-extraction",
"sentence-similarity"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/multi-qa-distilbert-dot-v1 | 102 | null | sentence-transformers | 4,564 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# multi-qa-distilbert-dot-v1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and was designed for **semantic search**... |
uer/chinese_roberta_L-4_H-128 | e962acf29bd006ef6d13106d63808ce82ad2688e | 2022-07-15T08:11:50.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-4_H-128 | 102 | null | transformers | 4,565 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
alefiury/wav2vec2-xls-r-300m-pt-br-spontaneous-speech-emotion-recognition | 909a1e8a60ce6143a121d36587c0bc10cf79d35c | 2022-04-03T12:38:09.000Z | [
"pytorch",
"wav2vec2",
"audio-classification",
"pt",
"dataset:coraa_ser",
"dataset:emovo",
"dataset:ravdess",
"dataset:baved",
"transformers",
"audio",
"speech",
"portuguese-speech-corpus",
"italian-speech-corpus",
"english-speech-corpus",
"arabic-speech-corpus",
"spontaneous",
"PyTo... | audio-classification | false | alefiury | null | alefiury/wav2vec2-xls-r-300m-pt-br-spontaneous-speech-emotion-recognition | 102 | null | transformers | 4,566 | ---
language: pt
datasets:
- coraa_ser
- emovo
- ravdess
- baved
metrics:
- f1
tags:
- audio
- speech
- wav2vec2
- pt
- portuguese-speech-corpus
- italian-speech-corpus
- english-speech-corpus
- arabic-speech-corpus
- spontaneous
- speech
- PyTorch
license: apache-2.0
model_index:
name: wav2vec2-xls-r-300m-pt-br-spon... |
microsoft/cvt-21 | 21534c74c3a738a096d7891ea674e2907b299ce6 | 2022-05-18T16:01:27.000Z | [
"pytorch",
"cvt",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2103.15808",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/cvt-21 | 102 | null | transformers | 4,567 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https... |
allenai/tk-instruct-large-def-pos | c7bf9e3da3c3a5f426d984af8473ac2b0960869a | 2022-05-27T06:31:27.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:natural instructions v2.0",
"arxiv:1910.10683",
"arxiv:2204.07705",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/tk-instruct-large-def-pos | 102 | null | transformers | 4,568 | ---
language: en
license: apache-2.0
datasets:
- natural instructions v2.0
---
# Model description
Tk-Instruct is a series of encoder-decoder Transformer models that are trained to solve various NLP tasks by following in-context instructions (plain language task definitions, k-shot examples, explanations, etc). Built... |
autoevaluate/extractive-question-answering | a1b9025ceb8c8e7c2b2a8a756c39d2a0f3d13d74 | 2022-07-20T13:18:04.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | autoevaluate | null | autoevaluate/extractive-question-answering | 102 | null | transformers | 4,569 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: extractive-question-answering
results: []
---
<!-- 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 com... |
facebook/levit-128 | 6b044a5ff3a3f662b44f1154934406cdc21029c2 | 2022-06-01T13:21:29.000Z | [
"pytorch",
"levit",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2104.01136",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/levit-128 | 102 | null | transformers | 4,570 |
---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: http... |
yanekyuk/bert-uncased-keyword-discriminator | 608355cf37247134d6f8e89368fae042cd939897 | 2022-06-06T09:27:17.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | yanekyuk | null | yanekyuk/bert-uncased-keyword-discriminator | 102 | null | transformers | 4,571 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
language:
- en
widget:
- text: "Broadcom agreed to acquire cloud computing company VMware in a $61 billion (€57bn) cash-and stock deal, massively diversifying the chipmaker’s business and almost tripling its software-re... |
facebook/roberta-hate-speech-dynabench-r4-target | 5de477c500cac9cb5865580f6355d5b048bcea1e | 2022-06-10T22:35:56.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"arxiv:2012.15761",
"transformers"
] | text-classification | false | facebook | null | facebook/roberta-hate-speech-dynabench-r4-target | 102 | null | transformers | 4,572 | ---
language: en
---
# LFTW R4 Target
The R4 Target model from [Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection](https://arxiv.org/abs/2012.15761)
## Citation Information
```bibtex
@inproceedings{vidgen2021lftw,
title={Learning from the Worst: Dynamically Generated Dataset... |
DTAI-KULeuven/robbertje-merged-dutch-sentiment | 57a25d121dc660786105af327d9c1070743ac7ce | 2022-06-29T13:12:48.000Z | [
"pytorch",
"roberta",
"text-classification",
"nl",
"dataset:dbrd",
"transformers",
"Dutch",
"Flemish",
"RoBERTa",
"RobBERT",
"license:mit",
"model-index"
] | text-classification | false | DTAI-KULeuven | null | DTAI-KULeuven/robbertje-merged-dutch-sentiment | 102 | null | transformers | 4,573 | ---
language: nl
license: mit
datasets:
- dbrd
model-index:
- name: robbertje-merged-dutch-sentiment
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: dbrd
type: sentiment-analysis
split: test
metrics:
- name: Accuracy
type: accuracy
... |
Helsinki-NLP/opus-mt-de-nl | da037ec1ad70f9d79735c287d418c00158b55b68 | 2021-09-09T21:32:35.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"nl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-nl | 101 | null | transformers | 4,574 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-de-nl
* source languages: de
* target languages: nl
* OPUS readme: [de-nl](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-nl/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-es-cs | afa3840361de865521e870a095d9a3441043e11a | 2021-09-09T21:41:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"cs",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-cs | 101 | null | transformers | 4,575 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-es-cs
* source languages: es
* target languages: cs
* OPUS readme: [es-cs](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-cs/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
VietAI/gpt-j-6B-vietnamese-news | 944f42f2483efdf17438fc905e08c96dcaa7ce94 | 2021-10-10T16:44:53.000Z | [
"pytorch",
"gptj",
"text-generation",
"vi",
"transformers",
"causal-lm"
] | text-generation | false | VietAI | null | VietAI/gpt-j-6B-vietnamese-news | 101 | 1 | transformers | 4,576 | ---
language:
- vi
tags:
- pytorch
- causal-lm
- text-generation
---
# GPT-J 6B for Vietnamese News
Details will be available soon.
For more information, please contact anhduongng.1001@gmail.com / imthanhlv@gmail.com / nguyenvulebinh@gmail.com. |
avichr/hebEMO_sadness | b8a411d091c6cd285a746631c20cf12dc8f0d61f | 2022-04-15T09:35:47.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | avichr | null | avichr/hebEMO_sadness | 101 | null | transformers | 4,577 | # HebEMO - Emotion Recognition Model for Modern Hebrew
<img align="right" src="https://github.com/avichaychriqui/HeBERT/blob/main/data/heBERT_logo.png?raw=true" width="250">
HebEMO is a tool that detects polarity and extracts emotions from modern Hebrew User-Generated Content (UGC), which was trained on a unique Covid... |
cankeles/ConvTasNet_WHAMR_enhsingle_16k | f47048acf872880e504bd92f4252f996d73c3024 | 2022-02-17T19:32:29.000Z | [
"pytorch",
"dataset:Libri1Mix",
"dataset:enh_single",
"asteroid",
"audio",
"ConvTasNet",
"audio-to-audio",
"license:cc-by-sa-4.0"
] | audio-to-audio | false | cankeles | null | cankeles/ConvTasNet_WHAMR_enhsingle_16k | 101 | 1 | asteroid | 4,578 | ---
tags:
- asteroid
- audio
- ConvTasNet
- audio-to-audio
datasets:
- Libri1Mix
- enh_single
license: cc-by-sa-4.0
---
## Asteroid model `cankeles/ConvTasNet_WHAMR_enhsingle_16k`
Description:
This model was fine tuned on a modified version of WHAMR! where the speakers were taken from audiobook recordings and reverb ... |
facebook/convnext-large-384-22k-1k | 2a166cf1cbb8b63652775179726b4da8747b312a | 2022-03-02T19:03:42.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-21k",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-large-384-22k-1k | 101 | null | transformers | 4,579 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-21k
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teap... |
hf-internal-testing/tiny-random-clip | 04b741590ff4e18ef4d778c72afe3ca3a680a0c7 | 2021-09-17T19:24:44.000Z | [
"pytorch",
"clip",
"transformers"
] | null | false | hf-internal-testing | null | hf-internal-testing/tiny-random-clip | 101 | null | transformers | 4,580 | Entry not found |
minimaxir/hacker-news | 87e129a1c04a499f390507d310d241aac4fa94f4 | 2021-05-23T09:35:33.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | minimaxir | null | minimaxir/hacker-news | 101 | 1 | transformers | 4,581 | Entry not found |
mmoradi/Robust-Biomed-RoBERTa-TextClassification | feb1f69fa6add99bd301aead3d520fc993f53dec | 2021-10-07T12:29:59.000Z | [
"pytorch",
"jax",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | mmoradi | null | mmoradi/Robust-Biomed-RoBERTa-TextClassification | 101 | null | transformers | 4,582 | Entry not found |
seyonec/BPE_SELFIES_PubChem_shard00_160k | c97e5b0f514e12056643f9582006305255eed97a | 2021-05-20T20:46:05.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | seyonec | null | seyonec/BPE_SELFIES_PubChem_shard00_160k | 101 | null | transformers | 4,583 | Entry not found |
stevhliu/astroGPT | b28e338b036f2540f0f024f8f297d106d05d8c54 | 2021-05-23T12:59:14.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"en",
"transformers"
] | text-generation | false | stevhliu | null | stevhliu/astroGPT | 101 | null | transformers | 4,584 | ---
language: "en"
thumbnail: "https://raw.githubusercontent.com/stevhliu/satsuma/master/images/astroGPT-thumbnail.png"
widget:
- text: "Jan 18, 2020"
- text: "Feb 14, 2020"
- text: "Jul 04, 2020"
---
# astroGPT 🪐
## Model description
This is a GPT-2 model fine-tuned on Western zodiac signs. For more information ab... |
inovex/multi2convai-logistics-pl-bert | 33b7a64302b6be766af6d73c3f653d2c6e19280b | 2022-03-01T08:54:40.000Z | [
"pytorch",
"bert",
"text-classification",
"pl",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-logistics-pl-bert | 101 | 2 | transformers | 4,585 | ---
tags:
- text-classification
widget:
- text: "gdzie mogę umieścić paczkę?"
license: mit
language: pl
---
# Multi2ConvAI-Logistics: finetuned Bert for Polish
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](https... |
patrickvonplaten/wav2vec2-large-960h-lv60-self-4-gram | a8959cb7bd04673d529b4d7b25c8a5ded2870399 | 2022-05-24T11:11:07.000Z | [
"pytorch",
"tf",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"transformers",
"audio",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-large-960h-lv60-self-4-gram | 101 | 1 | transformers | 4,586 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.huggingface.... |
Servinform/wav2vec2-large-xlsr-53-spanish | 718b1866141dfae432b6d00bddc87dee8ae89691 | 2022-05-24T12:58:17.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"transformers",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"lice... | automatic-speech-recognition | false | Servinform | null | Servinform/wav2vec2-large-xlsr-53-spanish | 101 | null | transformers | 4,587 | ---
language: es
license: apache-2.0
datasets:
- common_voice
- mozilla-foundation/common_voice_6_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- es
- hf-asr-leaderboard
- mozilla-foundation/common_voice_6_0
- robust-speech-event
- speech
- xlsr-fine-tuning-week
model-index:
- name: XLSR Wav2Vec2 ... |
ccdv/lsg-bart-base-4096-mediasum | 98a6a8ccfd37dedbf2619774ce9538db3064b603 | 2022-07-25T05:30:36.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:ccdv/mediasum",
"transformers",
"summarization",
"model-index",
"autotrain_compatible"
] | summarization | false | ccdv | null | ccdv/lsg-bart-base-4096-mediasum | 101 | null | transformers | 4,588 | ---
language:
- en
tags:
- summarization
datasets:
- ccdv/mediasum
metrics:
- rouge
model-index:
- name: ccdv/lsg-bart-base-4096-mediasum
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then r... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-poetry | bc50b6dc1c97dc66998287efb6d044bdaa8f7057 | 2021-10-17T12:09:38.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-ca-poetry | 100 | 2 | transformers | 4,589 | ---
language:
- ar
license: apache-2.0
widget:
- text: 'الخيل والليل والبيداء تعرفني [SEP] والسيف والرمح والقرطاس والقلم'
---
# CAMeLBERT-CA Poetry Classification Model
## Model description
**CAMeLBERT-CA Poetry Classification Model** is a poetry classification model that was built by fine-tuning the [CAMeLBERT Class... |
Helsinki-NLP/opus-mt-de-ar | 3abbe7441f40e0657e0dc3e99df5dcaeaa3d323b | 2021-01-18T07:57:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"ar",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-ar | 100 | null | transformers | 4,590 | ---
language:
- de
- ar
tags:
- translation
license: apache-2.0
---
### deu-ara
* source group: German
* target group: Arabic
* OPUS readme: [deu-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-ara/README.md)
* model: transformer-align
* source language(s): deu
* target language(... |
Helsinki-NLP/opus-mt-en-ga | f09be38231432610fe90281edb71b1b2f8d91355 | 2021-01-18T08:07:56.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ga",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ga | 100 | null | transformers | 4,591 | ---
language:
- en
- ga
tags:
- translation
license: apache-2.0
---
### eng-gle
* source group: English
* target group: Irish
* OPUS readme: [eng-gle](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-gle/README.md)
* model: transformer-align
* source language(s): eng
* target language(... |
JorisCos/DCCRNet_Libri1Mix_enhsingle_16k | 00914c64c47932a360b5b4e0c07ab12d305604ba | 2021-09-23T15:49:13.000Z | [
"pytorch",
"dataset:Libri1Mix",
"dataset:enh_single",
"asteroid",
"audio",
"DCCRNet",
"audio-to-audio",
"speech-enhancement",
"license:cc-by-sa-4.0"
] | audio-to-audio | false | JorisCos | null | JorisCos/DCCRNet_Libri1Mix_enhsingle_16k | 100 | 4 | asteroid | 4,592 | ---
tags:
- asteroid
- audio
- DCCRNet
- audio-to-audio
- speech-enhancement
datasets:
- Libri1Mix
- enh_single
license: cc-by-sa-4.0
---
## Asteroid model `JorisCos/DCCRNet_Libri1Mix_enhsignle_16k`
Description:
This model was trained by Joris Cosentino using the librimix recipe in [Asteroid](https://github.com/aste... |
KBLab/bert-base-swedish-cased-ner | 02bd6181e8c5aa0e6d4c5cd32fe68d5adfb75019 | 2022-06-07T20:08:35.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"sv",
"transformers",
"autotrain_compatible"
] | token-classification | false | KBLab | null | KBLab/bert-base-swedish-cased-ner | 100 | 3 | transformers | 4,593 | ---
language: sv
---
# Swedish BERT Models
The National Library of Sweden / KBLab releases three pretrained language models based on BERT and ALBERT. The models are trained on approximately 15-20GB of text (200M sentences, 3000M tokens) from various sources (books, news, government publications, swedish wikipedia and... |
TristanBehrens/js-fakes-4bars | 3d52a00e68108008a2fd2143b0a84b53c8e48f07 | 2022-01-11T07:12:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"music-modeling",
"music-generation"
] | text-generation | false | TristanBehrens | null | TristanBehrens/js-fakes-4bars | 100 | 4 | transformers | 4,594 | ---
tags:
- gpt2
- text-generation
- music-modeling
- music-generation
widget:
- text: "PIECE_START"
- text: "PIECE_START STYLE=JSFAKES GENRE=JSFAKES TRACK_START INST=48 BAR_START NOTE_ON=60"
- text: "PIECE_START STYLE=JSFAKES GENRE=JSFAKES TRACK_START INST=48 BAR_START NOTE_ON=58"
---
# GPT-2 for Music
Langua... |
avichr/hebEMO_anger | 396ae3c5162f891bbb3541c98d0bdf96c678413d | 2022-04-15T09:36:21.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | avichr | null | avichr/hebEMO_anger | 100 | null | transformers | 4,595 | # HebEMO - Emotion Recognition Model for Modern Hebrew
<img align="right" src="https://github.com/avichaychriqui/HeBERT/blob/main/data/heBERT_logo.png?raw=true" width="250">
HebEMO is a tool that detects polarity and extracts emotions from modern Hebrew User-Generated Content (UGC), which was trained on a unique Covid... |
avichr/hebEMO_disgust | 4ead9813ed4ce9643bd013aafb9a60228af3cc4c | 2022-04-15T09:35:32.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | avichr | null | avichr/hebEMO_disgust | 100 | null | transformers | 4,596 | # HebEMO - Emotion Recognition Model for Modern Hebrew
<img align="right" src="https://github.com/avichaychriqui/HeBERT/blob/main/data/heBERT_logo.png?raw=true" width="250">
HebEMO is a tool that detects polarity and extracts emotions from modern Hebrew User-Generated Content (UGC), which was trained on a unique Covid... |
chinhon/fake_tweet_detect | 8b0fd4fe93049f4679a2fd56080f6e4ef80fb2e2 | 2022-01-13T01:45:01.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | chinhon | null | chinhon/fake_tweet_detect | 100 | 1 | transformers | 4,597 | Entry not found |
cross-encoder/msmarco-MiniLM-L6-en-de-v1 | 368a0096bbd54a6850239d12068a1302c329cc40 | 2021-08-05T08:40:24.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:apache-2.0"
] | text-classification | false | cross-encoder | null | cross-encoder/msmarco-MiniLM-L6-en-de-v1 | 100 | null | transformers | 4,598 | ---
license: apache-2.0
---
# Cross-Encoder for MS MARCO - EN-DE
This is a cross-lingual Cross-Encoder model for EN-DE that can be used for passage re-ranking. It was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: ... |
gchhablani/bert-base-cased-finetuned-cola | 349865261dd2b7c18501a6662388d72e1aa981ec | 2021-09-20T09:07:12.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"en",
"dataset:glue",
"arxiv:2105.03824",
"transformers",
"generated_from_trainer",
"fnet-bert-base-comparison",
"license:apache-2.0",
"model-index"
] | text-classification | false | gchhablani | null | gchhablani/bert-base-cased-finetuned-cola | 100 | null | transformers | 4,599 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: bert-base-cased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE COLA
... |
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