modelId stringlengths 4 112 | sha stringlengths 40 40 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringclasses 29
values | private bool 1
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values | __index_level_0__ int64 0 38.5k | readme stringlengths 0 186k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
uw-madison/nystromformer-512 | 405ccb83538dd58b90104d20af1a08d901c103cd | 2022-01-11T14:13:39.000Z | [
"pytorch",
"nystromformer",
"fill-mask",
"arxiv:2102.03902",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uw-madison | null | uw-madison/nystromformer-512 | 418 | null | transformers | 2,500 | # Nyströmformer
Nyströmformer model for masked language modeling (MLM) pretrained on BookCorpus and English Wikipedia for sequence length 512.
## About Nyströmformer
The Nyströmformer model was proposed in [Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention](https://arxiv.org/abs/2102.03902) b... |
valurank/distilroberta-hatespeech | b15ea666a2455171fddf83640a469d74c73cb2fe | 2022-06-08T20:30:04.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/distilroberta-hatespeech | 418 | null | transformers | 2,501 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-hatespeech
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 comment. -->
# distilroberta-h... |
ccdv/lsg-bart-base-4096-multinews | 976609dd1abc5f229a55938023010466025b43ff | 2022-07-25T05:31:36.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:multi_news",
"transformers",
"summarization",
"model-index",
"autotrain_compatible"
] | summarization | false | ccdv | null | ccdv/lsg-bart-base-4096-multinews | 418 | null | transformers | 2,502 | ---
language:
- en
tags:
- summarization
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: ccdv/lsg-bart-base-4096-multinews
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 rem... |
mrm8488/bert-multi-cased-finedtuned-xquad-tydiqa-goldp | 759a6ee94fec457ac24857f387ec986bafe7e79e | 2021-05-20T00:27:53.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"multilingual",
"transformers",
"autotrain_compatible"
] | question-answering | false | mrm8488 | null | mrm8488/bert-multi-cased-finedtuned-xquad-tydiqa-goldp | 417 | 3 | transformers | 2,503 | ---
language: multilingual
thumbnail:
---
# A fine-tuned model on GoldP task from Tydi QA dataset
This model uses [bert-multi-cased-finetuned-xquadv1](https://huggingface.co/mrm8488/bert-multi-cased-finetuned-xquadv1) and fine-tuned on [Tydi QA](https://github.com/google-research-datasets/tydiqa) dataset for Gold Pas... |
valurank/distilroberta-offensive | 1ece43c97b555234c1a6bd96b04b157cb5b4daa5 | 2022-06-08T20:31:46.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/distilroberta-offensive | 417 | null | transformers | 2,504 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-offensive
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 comment. -->
# distilroberta-of... |
danielhou13/longformer-finetuned_papers_v2 | 4ee6b71b784563504145329e17dbf615a18e69d6 | 2022-06-28T18:10:53.000Z | [
"pytorch",
"longformer",
"text-classification",
"transformers"
] | text-classification | false | danielhou13 | null | danielhou13/longformer-finetuned_papers_v2 | 417 | null | transformers | 2,505 | Entry not found |
google/roberta2roberta_L-24_bbc | ea245d42ee17b2ade5e6197cee59e5060be120e4 | 2020-12-11T21:43:05.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"en",
"dataset:xsum",
"arxiv:1907.12461",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | google | null | google/roberta2roberta_L-24_bbc | 416 | 1 | transformers | 2,506 | ---
language: en
license: apache-2.0
datasets:
- xsum
tags:
- summarization
---
# Roberta2Roberta_L-24_bbc EncoderDecoder model
The model was introduced in
[this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.dev/google... |
hakurei/litv2-6B-rev2 | 5de12979db26d931ddf3cce2757a5dcb18354ec4 | 2022-06-17T04:51:39.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | hakurei | null | hakurei/litv2-6B-rev2 | 416 | null | transformers | 2,507 | https://wandb.ai/haruu/mesh-transformer-jax/runs/3u6yrxfv |
NTQAI/wav2vec2-large-japanese | cce86173b9b0eceb0fa3f9172b1fe5c04647bdeb | 2021-07-12T04:12:29.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ja",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"model-index"
] | automatic-speech-recognition | false | NTQAI | null | NTQAI/wav2vec2-large-japanese | 415 | 4 | transformers | 2,508 | ---
language: ja
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
model-index:
- name: Wav2Vec2 Japanese by NTQAI
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice ja
type: common_... |
bond005/wav2vec2-large-ru-golos | 414e4b3c42f74aa71392573715f6939154a8fb50 | 2022-06-21T20:08:07.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:SberDevices/Golos",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | bond005 | null | bond005/wav2vec2-large-ru-golos | 415 | null | transformers | 2,509 | ---
language: ru
datasets:
- SberDevices/Golos
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Russian by Ivan Bondarenko
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition... |
Davlan/xlm-roberta-base-finetuned-amharic | 238236a3b2b9ba6ff7bb7af888d614345e8d8842 | 2021-06-05T20:37:25.000Z | [
"pytorch",
"xlm-roberta",
"fill-mask",
"am",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Davlan | null | Davlan/xlm-roberta-base-finetuned-amharic | 414 | null | transformers | 2,510 | Hugging Face's logo
---
language: am
datasets:
---
# xlm-roberta-base-finetuned-amharic
## Model description
**xlm-roberta-base-finetuned-amharic** is a **Amharic RoBERTa** model obtained by fine-tuning **xlm-roberta-base** model on Amharic language texts. It provides **better performance** than the XLM-RoBERTa on na... |
cambridgeltl/mirror-bert-base-uncased-sentence | 3d330e362b17625bc507197dad8cd0e9b242f25e | 2021-09-19T22:47:28.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:2104.08027",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/mirror-bert-base-uncased-sentence | 414 | null | transformers | 2,511 | ---
language: en
tags:
- sentence-embeddings
- sentence-similarity
### cambridgeltl/mirror-bert-base-uncased-sentence
An unsupervised sentence encoder proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2104.08027.pdf). Trained with unlabelled raw sentences, using [bert-base-uncased](https://huggingface.co/bert-bas... |
kykim/bertshared-kor-base | 8ea27677d006a547aee2a7753d1ff18a0346860c | 2021-02-23T11:49:50.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"ko",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | kykim | null | kykim/bertshared-kor-base | 414 | 1 | transformers | 2,512 | ---
language: ko
---
# Bert base model for Korean
* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in [github](https://github.com/kiyoungkim1/LM-kor)
```python
# only for pytorch in transformers
from transformers import BertTokenize... |
valurank/distilroberta-proppy | 4740f6aacb2cee756f792793c86736b845ea2650 | 2022-06-08T20:38:27.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/distilroberta-proppy | 414 | null | transformers | 2,513 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-proppy
results: []
---
# distilroberta-proppy
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the proppy corpus.
It achieves the following results on the evaluation set:
- L... |
allenai/PRIMERA-arxiv | 179e7c74d592955689b69a91f033ec4212eba52e | 2022-06-01T22:30:16.000Z | [
"pytorch",
"led",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/PRIMERA-arxiv | 414 | null | transformers | 2,514 | ---
license: apache-2.0
---
HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022).
The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in the original github rep... |
eleldar/language-detection | 735cc09f01b8b4d831228e0fa7640464e56a022e | 2022-05-24T10:06:00.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"text-classification",
"arxiv:1911.02116",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | eleldar | null | eleldar/language-detection | 414 | 1 | transformers | 2,515 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-language-detection
results: []
---
# Clone from [https://huggingface.co/papluca/xlm-roberta-base-language-detection](xlm-roberta-base-language-detection)
This model is a fine-tuned version of [xlm-roberta-... |
JorisCos/ConvTasNet_Libri2Mix_sepclean_16k | e1ef95ab7a037950f3a606b9a56760cf94701d3d | 2021-09-23T15:48:54.000Z | [
"pytorch",
"dataset:Libri2Mix",
"dataset:sep_clean",
"asteroid",
"audio",
"ConvTasNet",
"audio-to-audio",
"license:cc-by-sa-4.0"
] | audio-to-audio | false | JorisCos | null | JorisCos/ConvTasNet_Libri2Mix_sepclean_16k | 413 | 1 | asteroid | 2,516 | ---
tags:
- asteroid
- audio
- ConvTasNet
- audio-to-audio
datasets:
- Libri2Mix
- sep_clean
license: cc-by-sa-4.0
---
## Asteroid model `JorisCos/ConvTasNet_Libri2Mix_sepclean_16k`
Description:
This model was trained by Joris Cosentino using the librimix recipe in [Asteroid](https://github.com/asteroid-team/asteroi... |
ckiplab/albert-tiny-chinese-pos | 0759335eb37766726e12e173bd422237b70ad377 | 2022-05-10T03:28:11.000Z | [
"pytorch",
"albert",
"token-classification",
"zh",
"transformers",
"license:gpl-3.0",
"autotrain_compatible"
] | token-classification | false | ckiplab | null | ckiplab/albert-tiny-chinese-pos | 413 | null | transformers | 2,517 | ---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- albert
- zh
license: gpl-3.0
---
# CKIP ALBERT Tiny Chinese
This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word seg... |
facebook/maskformer-swin-small-coco | 3b42291baa14175ec3b47525de9c7e61f72c3ab7 | 2022-04-04T16:01:56.000Z | [
"pytorch",
"maskformer",
"dataset:coco",
"arxiv:2107.06278",
"transformers",
"vision",
"image-segmentatiom",
"license:apache-2.0"
] | null | false | facebook | null | facebook/maskformer-swin-small-coco | 413 | null | transformers | 2,518 | ---
license: apache-2.0
tags:
- vision
- image-segmentatiom
datasets:
- coco
---
# Mask
Mask model trained on coco. It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/f... |
rjbownes/Magic-The-Generating | 07237dc6dfab8654be4ffd6e067e4671726420b5 | 2021-05-23T12:17:20.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | rjbownes | null | rjbownes/Magic-The-Generating | 412 | null | transformers | 2,519 | ---
widget:
- text: "Even the Dwarves"
- text: "The secrets of"
---
# Model name
Magic The Generating
## Model description
This is a fine tuned GPT-2 model trained on a corpus of all available English language Magic the Gathering card flavour texts.
## Intended uses & limitations
This is intended only for use in g... |
valurank/distilroberta-propaganda-2class | 7f136a28a2485f117da9b2dd5612f0f2a506a07b | 2022-06-08T20:39:15.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/distilroberta-propaganda-2class | 412 | 1 | transformers | 2,520 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-propaganda-2class
results: []
---
# distilroberta-propaganda-2class
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the QCRI propaganda dataset.
It achieves the following r... |
ishan/bert-base-uncased-mnli | d88bc3e2a64c17016f3638b1c5379d8709a1d3d7 | 2021-05-19T20:32:21.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"dataset:MNLI",
"arxiv:1810.04805",
"transformers"
] | text-classification | false | ishan | null | ishan/bert-base-uncased-mnli | 411 | 1 | transformers | 2,521 | ---
language: en
thumbnail:
tags:
- pytorch
- text-classification
datasets:
- MNLI
---
# bert-base-uncased finetuned on MNLI
## Model Details and Training Data
We used the pretrained model from [bert-base-uncased](https://huggingface.co/bert-base-uncased) and finetuned it on [MultiNLI](https://cims.nyu.edu/~sbowman... |
sentence-transformers/paraphrase-albert-base-v2 | ba7fa0a9a209d687c911afb21ced12769ac05c7e | 2022-06-15T22:21:37.000Z | [
"pytorch",
"tf",
"albert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/paraphrase-albert-base-v2 | 411 | null | sentence-transformers | 2,522 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-albert-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional de... |
unc-nlp/lxmert-vqa-uncased | 945e6172c6c93befbe8d64683f22d34cb567e8ab | 2020-09-10T17:57:42.000Z | [
"pytorch",
"lxmert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | unc-nlp | null | unc-nlp/lxmert-vqa-uncased | 411 | null | transformers | 2,523 | Entry not found |
QuoQA-NLP/KE-T5-En2Ko-Base | 3a4e5fdb3663e678336c7dce8df1e46cae889c68 | 2022-07-08T22:35:14.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | QuoQA-NLP | null | QuoQA-NLP/KE-T5-En2Ko-Base | 411 | null | transformers | 2,524 | Entry not found |
HooshvareLab/albert-fa-zwnj-base-v2 | 2315c0d4ddd6bd68f7703c5651978706bf8aff37 | 2021-03-16T16:36:38.000Z | [
"pytorch",
"tf",
"albert",
"fill-mask",
"fa",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | HooshvareLab | null | HooshvareLab/albert-fa-zwnj-base-v2 | 410 | null | transformers | 2,525 | ---
language: fa
license: apache-2.0
---
# ALBERT-Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
> Call it little_berty
### BibTeX entry and citation info
Please cite in your publication as the following:
```bibtex
@misc{ALBERTPe... |
mrm8488/t5-base-finetuned-imdb-sentiment | d9d412418ff1a359b7783eeebd5b318791f00765 | 2020-12-11T21:55:46.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:imdb",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-imdb-sentiment | 408 | null | transformers | 2,526 | ---
language: en
datasets:
- imdb
---
# T5-base fine-tuned for Sentiment Anlalysis 🎞️👍👎
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) base fine-tuned on [IMDB](https://huggingface.co/datasets/imdb) dataset for **Sentiment Analysis** downstream task.
## Details of T5
T... |
salesken/xlm-roberta-base-finetuned-mnli-cross-lingual-transfer | 713c697b0cc891f9d05642592426678786293828 | 2021-07-21T09:25:02.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"dataset:mnli",
"dataset:xnli",
"transformers",
"sentence-similarity",
"zero-shot-classification",
"salesken",
"hindi",
"cross-lingual"
] | text-classification | false | salesken | null | salesken/xlm-roberta-base-finetuned-mnli-cross-lingual-transfer | 408 | 1 | transformers | 2,527 | ---
datasets:
- mnli
- xnli
tags:
- sentence-similarity
- transformers
- text-classification
- zero-shot-classification
- salesken
- hindi
- cross-lingual
inference: false
---
# XLM-R Base
A multilingual model is pre-trained on text coming from a mix of languages. We will look at a multilingual model called XLM-R fro... |
sshleifer/distilbart-xsum-6-6 | 9a31391363021090d1fceb38a9c83ecd0d0dc020 | 2021-06-14T08:25:26.000Z | [
"pytorch",
"jax",
"bart",
"text2text-generation",
"en",
"dataset:cnn_dailymail",
"dataset:xsum",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | sshleifer | null | sshleifer/distilbart-xsum-6-6 | 408 | null | transformers | 2,528 | ---
language: en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
- xsum
thumbnail: https://huggingface.co/front/thumbnails/distilbart_medium.png
---
### Usage
This checkpoint should be loaded into `BartForConditionalGeneration.from_pretrained`. See the [BART docs](https://huggingface.co/transforme... |
squirro/albert-base-v2-squad_v2 | f64291edf2204d5c9044c2d45867cf31bab5e054 | 2022-06-29T08:54:25.000Z | [
"pytorch",
"tf",
"onnx",
"albert",
"question-answering",
"en",
"dataset:squad_v2",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | squirro | null | squirro/albert-base-v2-squad_v2 | 408 | 1 | transformers | 2,529 | ---
license: apache-2.0
language: en
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: albert-base-v2-squad_v2
results:
- task:
name: Question Answering
type: question-answering
dataset:
type: squad_v2 # Required. Example: common_voice. Use dataset id from https://hf.co... |
Sheel/DialoGPT-small-harrypotter | 446603b6bad1a87aea7e0c7124b79773337ade93 | 2021-10-24T22:13:24.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Sheel | null | Sheel/DialoGPT-small-harrypotter | 407 | null | transformers | 2,530 | ---
tags:
- conversational
---
# Harry Potter DialGPT Model |
pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP | 1d9bf246aabd98e00bf6af2c70470801f86d4249 | 2022-07-26T00:01:00.000Z | [
"pytorch",
"longt5",
"text2text-generation",
"dataset:kmfoda/booksum",
"transformers",
"summarization",
"summary",
"booksum",
"long-document",
"long-form",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | pszemraj | null | pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP | 407 | 0 | transformers | 2,531 | ---
tags:
- summarization
- summary
- booksum
- long-document
- long-form
license: apache-2.0
datasets:
- kmfoda/booksum
metrics:
- rouge
inference: False
model-index:
- name: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP
results:
- task:
type: summarization
name: Summarization
dataset:... |
WangZeJun/simbert-base-chinese | b5c82a8ab1e4bcac799620fc4d870aae087b0c71 | 2022-06-14T09:17:59.000Z | [
"pytorch",
"transformers"
] | null | false | WangZeJun | null | WangZeJun/simbert-base-chinese | 406 | 2 | transformers | 2,532 | https://github.com/zejunwang1/bert4vec |
ethanyt/guwen-ner | 591273ff61bb5eb453f47c300f577058d6d2ee15 | 2021-06-17T09:23:09.000Z | [
"pytorch",
"jax",
"roberta",
"token-classification",
"zh",
"transformers",
"chinese",
"classical chinese",
"literary chinese",
"ancient chinese",
"bert",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | ethanyt | null | ethanyt/guwen-ner | 405 | 2 | transformers | 2,533 | ---
language:
- "zh"
thumbnail: "https://user-images.githubusercontent.com/9592150/97142000-cad08e00-179a-11eb-88df-aff9221482d8.png"
tags:
- "chinese"
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "bert"
- "pytorch"
license: "apache-2.0"
pipeline_tag: "token-classification"
widget:
- text: "及秦始皇，灭先... |
google/pegasus-wikihow | 3243b584d0d8cdc6e1a28ffd2ec73b623818b2da | 2020-10-22T16:33:36.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"arxiv:1912.08777",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | google | null | google/pegasus-wikihow | 405 | null | transformers | 2,534 | ---
language: en
tags:
- summarization
---
### Pegasus Models
See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
Original TF 1 code [here](https://github.com/google-research/pegasus)
Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019
Maintained by: [@... |
google/tapas-small | 856e82f8bad889c575161ea1752c67dd852f56a8 | 2021-11-29T10:12:54.000Z | [
"pytorch",
"tf",
"tapas",
"feature-extraction",
"en",
"arxiv:2004.02349",
"arxiv:2010.00571",
"transformers",
"TapasModel",
"license:apache-2.0"
] | feature-extraction | false | google | null | google/tapas-small | 405 | null | transformers | 2,535 | ---
language: en
tags:
- tapas
- TapasModel
license: apache-2.0
---
# TAPAS small model
This model has 2 versions which can be used. The latest version, which is the default one, corresponds to the `tapas_inter_masklm_small_reset` checkpoint of the [original Github repository](https://github.com/google-research/tap... |
ionite/DialoGPT-large-Sh0rtiAI-v2 | 83acb3785e6f4c0d6aa99d885a8970ac522ca556 | 2021-12-02T15:38:29.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ionite | null | ionite/DialoGPT-large-Sh0rtiAI-v2 | 405 | null | transformers | 2,536 | ---
tags:
- conversational
---
# Sh0rtiAI v2 DialoGPT Model |
EMBEDDIA/sloberta | 49db152a3bea54016773be3cce126a9b5ece88da | 2021-11-24T13:46:22.000Z | [
"pytorch",
"camembert",
"fill-mask",
"sl",
"transformers",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | EMBEDDIA | null | EMBEDDIA/sloberta | 404 | 1 | transformers | 2,537 | ---
language:
- sl
license: cc-by-sa-4.0
---
# Usage
Load in transformers library with:
```
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/sloberta")
model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/sloberta")
```
# SloBERTa
SloBERTa mod... |
jonatasgrosman/wav2vec2-xls-r-1b-english | 26ddad7c80aa4b7b5799540bd6c4c46c52c36789 | 2022-07-27T23:39:32.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-xls-r-1b-english | 403 | 5 | transformers | 2,538 | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- en
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R Wav2Vec2 English by Jonatas Grosman
results:
- task:
name: Automatic Spee... |
veb/twitch-bert-base-cased-pytorch | d611ffd8bdcf38b9268516638f959eb933480c21 | 2022-06-26T20:10:03.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | veb | null | veb/twitch-bert-base-cased-pytorch | 403 | null | transformers | 2,539 | Entry not found |
GamerMan02/DialoGPT-medium-gamerbot | 9fcfcfb417f37dbc0cac4d096d15cb00783d02d2 | 2021-09-22T00:52:35.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | GamerMan02 | null | GamerMan02/DialoGPT-medium-gamerbot | 402 | null | transformers | 2,540 | ---
tags:
- conversational
---
# Gamer Bot DialoGPT Model |
google/realm-cc-news-pretrained-encoder | 6dfb09adaa0c6f7f4b5df1ee4a6cff0fea111ad2 | 2022-01-06T06:25:03.000Z | [
"pytorch",
"realm",
"en",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/realm-cc-news-pretrained-encoder | 402 | null | transformers | 2,541 | ---
language: en
license: apache-2.0
---
# realm-cc-news-pretrained-encoder
## Model description
The REALM checkpoint pretrained with CC-News as target corpus and Wikipedia as knowledge corpus, converted from the TF checkpoint provided by Google Language.
The original paper, code, and checkpoints can be found [here... |
monologg/koelectra-base-finetuned-naver-ner | f30657e8e2330e1010ac9cf37e970afe4349c36b | 2020-05-13T03:51:43.000Z | [
"pytorch",
"electra",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | monologg | null | monologg/koelectra-base-finetuned-naver-ner | 402 | null | transformers | 2,542 | Entry not found |
raynardj/classical-chinese-punctuation-guwen-biaodian | 2f8c9ca2293102348c5d4dd2f4c95c6b760a135a | 2021-11-29T14:39:52.000Z | [
"pytorch",
"bert",
"token-classification",
"zh",
"transformers",
"ner",
"punctuation",
"古文",
"文言文",
"ancient",
"classical",
"autotrain_compatible"
] | token-classification | false | raynardj | null | raynardj/classical-chinese-punctuation-guwen-biaodian | 402 | 3 | transformers | 2,543 | ---
language:
- zh
tags:
- ner
- punctuation
- 古文
- 文言文
- ancient
- classical
widget:
- text: "郡邑置夫子庙于学以嵗时释奠盖自唐贞观以来未之或改我宋有天下因其制而损益之姑苏当浙右要区规模尤大更建炎戎马荡然无遗虽修学宫于荆榛瓦砾之余独殿宇未遑议也每春秋展礼于斋庐已则置不问殆为阙典今寳文阁直学士括苍梁公来牧之明年实绍兴十有一禩也二月上丁修祀既毕乃愓然自咎揖诸生而告之曰天子不以汝嘉为不肖俾再守兹土顾治民事神皆守之职惟是夫子之祀教化所基尤宜严且谨而拜跪荐祭之地卑陋乃尔其何以掲防妥灵汝嘉不敢避其责曩常去此弥年若有所负尚安得以罢輭自恕复累后人乎他日或克... |
Kargan/DialoGPT-small-randombot | f096b26cf579dbcaa641933b8dd710629165ac7a | 2021-08-29T12:13:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Kargan | null | Kargan/DialoGPT-small-randombot | 401 | null | transformers | 2,544 | ---
tags:
- conversational
---
# randombot DialoGPT Model |
bhadresh-savani/distilbert-base-uncased-go-emotion | b6878efeb9579da3a30627af1502446a99612acd | 2021-11-30T08:19:23.000Z | [
"pytorch",
"distilbert",
"en",
"dataset:go_emotions",
"transformers",
"text-classification",
"go-emotion",
"license:apache-2.0"
] | text-classification | false | bhadresh-savani | null | bhadresh-savani/distilbert-base-uncased-go-emotion | 401 | null | transformers | 2,545 | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- go-emotion
- pytorch
license: apache-2.0
datasets:
- go_emotions
metrics:
- Accuracy
---
# Distilbert-Base-Uncased-Go-Emotion
## Model description:
**Not ... |
matthewburke/korean_sentiment | 87ed5cf5710f0edd497b22057d37fbdb23a1ed12 | 2022-01-16T02:31:37.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers"
] | text-classification | false | matthewburke | null | matthewburke/korean_sentiment | 401 | 1 | transformers | 2,546 | ```
from transformers import pipeline
classifier = pipeline("text-classification", model="matthewburke/korean_sentiment")
custom_tweet = "영화 재밌다."
preds = classifier(custom_tweet, return_all_scores=True)
is_positive = preds[0][1]['score'] > 0.5
```
|
textattack/bert-base-uncased-WNLI | 78c56d02e40a1896f7d025185d2f9cbe0bd26c08 | 2021-05-20T07:39:22.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/bert-base-uncased-WNLI | 400 | null | transformers | 2,547 | ## TextAttack Model Card
This `bert-base-uncased` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 64, a learning
rate of 5e-05, and a maximum sequence length of 256.
Since this was a cla... |
af1tang/personaGPT | 7b13971b89d90dd252d0b372e2c87d4b2d16ccb7 | 2021-09-07T02:44:38.000Z | [
"pytorch",
"gpt2",
"text-generation",
"arxiv:1801.07243",
"transformers",
"conversational",
"license:gpl-3.0"
] | conversational | false | af1tang | null | af1tang/personaGPT | 399 | 7 | transformers | 2,548 | ---
tags:
- conversational
license: gpl-3.0
---
## A conversational agent with many personalities (PersonaGPT)
PersonaGPT is an open-domain conversational agent designed to do 2 tasks:
1. decoding _personalized_ responses based on input personality facts (the "persona" profile of the bot).
2. incorporating _turn-leve... |
pedropei/aspect-level-certainty | 746a61d07fd783be87b474dfdc76594caf6c125d | 2021-09-29T05:44:59.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pedropei | null | pedropei/aspect-level-certainty | 399 | null | transformers | 2,549 | Entry not found |
uer/roberta-medium-word-chinese-cluecorpussmall | f001eef673cf1ac1908a23944f8309ffbeb22bd9 | 2022-02-19T15:58:31.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/roberta-medium-word-chinese-cluecorpussmall | 399 | 1 | transformers | 2,550 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "最近一趟去北京的[MASK]几点发车"
---
# Chinese word-based RoBERTa Miniatures
## Model description
This is the set of 5 Chinese word-based RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/... |
GanjinZero/coder_all | 025b05d653a9e637cd708a68673f5edea92113a4 | 2022-04-25T02:20:33.000Z | [
"pytorch",
"bert",
"feature-extraction",
"en",
"transformers",
"biomedical",
"license:apache-2.0"
] | feature-extraction | false | GanjinZero | null | GanjinZero/coder_all | 398 | 1 | transformers | 2,551 | ---
language:
- en
license: apache-2.0
tags:
- bert
- biomedical
---
CODER: Knowledge infused cross-lingual medical term embedding for term normalization.
Multi lingual Version.
```
@article{YUAN2022103983,
title = {CODER: Knowledge-infused cross-lingual medical term embedding for term normalization},
journal = ... |
deepmind/vision-perceiver-fourier | 6900e2e595f397e6d7955db5234e13f2ad6ed67b | 2021-12-11T13:13:25.000Z | [
"pytorch",
"perceiver",
"image-classification",
"dataset:imagenet",
"arxiv:2107.14795",
"transformers",
"license:apache-2.0"
] | image-classification | false | deepmind | null | deepmind/vision-perceiver-fourier | 398 | 1 | transformers | 2,552 | ---
license: apache-2.0
tags:
datasets:
- imagenet
---
# Perceiver IO for vision (fixed Fourier position embeddings)
Perceiver IO model pre-trained on ImageNet (14 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Perceiver IO: A General Architecture for Structured Inputs & Outputs... |
gary109/ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-2 | a672eba7b1d471999106c564152c0364c7e25d35 | 2022-06-30T02:25:27.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"gary109/AI_Light_Dance",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | gary109 | null | gary109/ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-2 | 398 | 1 | transformers | 2,553 | ---
tags:
- automatic-speech-recognition
- gary109/AI_Light_Dance
- generated_from_trainer
model-index:
- name: ai-light-dance_singing2_ft_wav2vec2-large-xlsr-53-5gram-v4-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... |
mrm8488/bert2bert-spanish-question-generation | a56aa478647ae3a126cf20fc0a232ed74a2e7f9c | 2021-04-24T16:18:25.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"es",
"transformers",
"spanish",
"question",
"generation",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/bert2bert-spanish-question-generation | 397 | 5 | transformers | 2,554 |
---
language: es
tags:
- spanish
- question
- generation
widget:
- text: "Manuel vive en Murcia, España"
---
# Spanish Bert2Bert fine-tuned on SQuaD (es) for question generation |
sentence-transformers/msmarco-roberta-base-ance-firstp | 236d631f5a757abdb6ce28471648d964d9acb8f3 | 2022-06-15T23:03:19.000Z | [
"pytorch",
"tf",
"roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/msmarco-roberta-base-ance-firstp | 397 | null | sentence-transformers | 2,555 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# sentence-transformers/msmarco-roberta-base-ance-firstp
This is a port of the [ANCE FirstP Model](https://github.com/microsoft/ANCE/) to [sentence-transformers](https://www.SBERT.net... |
typeform/squeezebert-mnli | 040a407be7c792333d387d7c5d7ba2d3d1271256 | 2021-02-13T19:41:31.000Z | [
"pytorch",
"squeezebert",
"en",
"dataset:mulit_nli",
"transformers",
"zero-shot-classification"
] | zero-shot-classification | false | typeform | null | typeform/squeezebert-mnli | 397 | 1 | transformers | 2,556 | ---
language: en
pipeline_tag: zero-shot-classification
tags:
- squeezebert
datasets:
- mulit_nli
metrics:
- accuracy
---
# SqueezeBERT |
facebook/data2vec-audio-large-960h | 27aba26eed532b86dcd0f17284a0307de4b51f39 | 2022-06-06T10:36:59.000Z | [
"pytorch",
"data2vec-audio",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2202.03555",
"transformers",
"speech",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | facebook | null | facebook/data2vec-audio-large-960h | 397 | 5 | transformers | 2,557 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
- 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.co/speech_samples/sample2.fla... |
Unbabel/gec-t5_small | c958d53bfbce19c87342b69fc6bcaba7303d076f | 2021-09-27T11:27:48.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:clang-8",
"dataset:conll-14",
"dataset:conll-13",
"arxiv:2106.03830",
"transformers",
"grammatical error correction",
"text2text",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | Unbabel | null | Unbabel/gec-t5_small | 396 | 9 | transformers | 2,558 | ---
language:
- en
tags:
- grammatical error correction
- text2text
- t5
license: apache-2.0
datasets:
- clang-8
- conll-14
- conll-13
metrics:
- f0.5
---
This model is an implementation of the paper [A Simple Recipe for Multilingual Grammatical Error Correction](https://arxiv.org/pdf/2106.03830.pdf) from Google where... |
aryanbhosale/smartharrypotterbot | bd43c31a27c9610a9ec2e3125a460c14f4f60093 | 2022-03-04T15:41:28.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:mit"
] | conversational | false | aryanbhosale | null | aryanbhosale/smartharrypotterbot | 396 | null | transformers | 2,559 | |
albert-large-v1 | 17aeb59edfd7c7732fb96248a95f5c271a9fa28f | 2021-01-13T15:29:06.000Z | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | null | null | albert-large-v1 | 394 | null | transformers | 2,560 | ---
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# ALBERT Large v1
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-res... |
microsoft/prophetnet-large-uncased-cnndm | e827ade610c20cb825e0734d9f9b95fd4558b9e1 | 2021-01-17T13:15:58.000Z | [
"pytorch",
"rust",
"prophetnet",
"text2text-generation",
"en",
"dataset:cnn_dailymail",
"arxiv:2001.04063",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | microsoft | null | microsoft/prophetnet-large-uncased-cnndm | 394 | null | transformers | 2,561 | ---
language: en
datasets:
- cnn_dailymail
---
## prophetnet-large-uncased-cnndm
Fine-tuned weights(converted from [original fairseq version repo](https://github.com/microsoft/ProphetNet)) for [ProphetNet](https://arxiv.org/abs/2001.04063) on summarization task CNN/DailyMail.
ProphetNet is a new pre-trained language... |
mrm8488/t5-base-finetuned-break_data | 07edfcf30acbd71b19c849029bd1cd7990fe6a37 | 2021-10-20T08:31:28.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:break_data",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-break_data | 394 | 1 | transformers | 2,562 | ---
language: en
datasets:
- break_data
widget:
- text: "paraphrase: The composer of Sands Theme plays what type of guitar?"
---
# T5-base fine-tuned on break_data / QDMR-high-level ❓➡️📋
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned on [break_data](https://huggi... |
ArthurZ/jukebox-1b-lyrics | a0fe6d15e4a6de89f6447b1ae4e0ca5d16647b63 | 2022-07-19T09:40:53.000Z | [
"pytorch",
"jukebox",
"arxiv:2005.00341",
"transformers",
"MusicGeneration"
] | null | false | ArthurZ | null | ArthurZ/jukebox-1b-lyrics | 394 | 3 | transformers | 2,563 | ---
tags:
- MusicGeneration
- jukebox
---
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
... |
yanekyuk/bert-keyword-extractor | 9aff81f51327c2effea96fb1a928a2e58fd0cfe7 | 2022-06-04T00:51:39.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | yanekyuk | null | yanekyuk/bert-keyword-extractor | 394 | 1 | transformers | 2,564 | ---
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... |
Helsinki-NLP/opus-mt-jap-en | 797a0fff3eda86b8c059bd9b04943accf9e5b19a | 2021-09-10T13:53:31.000Z | [
"pytorch",
"marian",
"text2text-generation",
"jap",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-jap-en | 393 | null | transformers | 2,565 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-jap-en
* source languages: jap
* target languages: en
* OPUS readme: [jap-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/jap-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
cambridgeltl/mirror-roberta-base-sentence | 3689dff45b000d88e959008d0f64a3e420b142d4 | 2021-09-19T22:48:01.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"arxiv:2104.08027",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/mirror-roberta-base-sentence | 393 | null | transformers | 2,566 | ---
language: en
tags:
- sentence-embeddings
- sentence-similarity
### cambridgeltl/mirror-roberta-base-sentence
An unsupervised sentence encoder proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2104.08027.pdf). The model is trained with unlabelled raw sentences, using [roberta-base](https://huggingface.co/rober... |
Geotrend/bert-base-fr-cased | ab40c6b5f1f03e9fa8d11492b293d3599233f746 | 2021-05-18T19:56:16.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"fr",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-fr-cased | 392 | null | transformers | 2,567 | ---
language: fr
datasets: wikipedia
license: apache-2.0
widget:
- text: "Paris est la [MASK] de la France."
- text: "Paris est la capitale de la [MASK]."
- text: "L'élection américaine a eu [MASK] en novembre 2020."
---
# bert-base-fr-cased
We are sharing smaller versions of [bert-base-multilingual-cased](https:/... |
algoprog/mimics-tagging-roberta-base | dba82c959fdddf55ba244a96f242858490b4006b | 2022-02-24T01:14:23.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | algoprog | null | algoprog/mimics-tagging-roberta-base | 392 | null | transformers | 2,568 | Entry not found |
google/pegasus-gigaword | e485c6799ef3d0b03992d364b205e92f6cb67656 | 2021-07-21T21:25:28.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"dataset:gigaword",
"arxiv:1912.08777",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | google | null | google/pegasus-gigaword | 392 | null | transformers | 2,569 | ---
language: en
tags:
- summarization
datasets:
- gigaword
---
### Pegasus Models
See Docs: [here](https://huggingface.co/transformers/master/model_doc/pegasus.html)
Original TF 1 code [here](https://github.com/google-research/pegasus)
Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 20... |
Akito1961/DialoGPT-small-C3PO | 9bc75e4cbbdb460ec0d46986128d159d0ad1cddc | 2022-07-03T10:31:23.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Akito1961 | null | Akito1961/DialoGPT-small-C3PO | 392 | null | transformers | 2,570 | ---
tags:
- conversational
---
# C3PO DialoGPT Small |
Helsinki-NLP/opus-mt-it-de | db0cf30d9edbe6569fdcc25ff08c03bbcdf9b22f | 2021-09-10T13:52:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"it",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-it-de | 391 | null | transformers | 2,571 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-it-de
* source languages: it
* target languages: de
* OPUS readme: [it-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/it-de/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
cointegrated/roberta-base-formality | 7787b6bde0a58bcb35902a8bbf29909f76b7eea2 | 2021-10-17T17:27:50.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | cointegrated | null | cointegrated/roberta-base-formality | 391 | null | transformers | 2,572 | Entry not found |
facebook/convnext-base-224 | eda2970bc74154a2af92300316deecd49f72bea8 | 2022-02-26T12:16:30.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-base-224 | 391 | 2 | transformers | 2,573 | ---
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... |
facebook/wav2vec2-conformer-rope-large-960h-ft | 92f0f25475761ebe67e8e617c99450f04ff68c37 | 2022-06-15T08:12:26.000Z | [
"pytorch",
"wav2vec2-conformer",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2010.05171",
"transformers",
"speech",
"audio",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-conformer-rope-large-960h-ft | 391 | 3 | transformers | 2,574 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
model-index:
- name: wav2vec2-conformer-rel-pos-large-960h-ft
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
... |
Kirili4ik/ruDialoGpt3-medium-finetuned-telegram | 6625aee6169f5087a7dccc47ded8906c44478ecf | 2022-01-14T15:33:37.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"ru-RU",
"transformers",
"conversational"
] | conversational | false | Kirili4ik | null | Kirili4ik/ruDialoGpt3-medium-finetuned-telegram | 390 | 5 | transformers | 2,575 | ---
language:
- ru
- ru-RU
tags:
- conversational
---
### 📝 Description
DialoGPT trained on Russian language and fine tuned on my telegram chat.
This model was created by [sberbank-ai](https://hf.co/sberbank-ai) and trained on Russian forums (see [Grossmend's model](https://hf.co/Grossmend/rudialogpt3_medium_base... |
KoboldAI/fairseq-dense-6.7B | 634af26aec93133afc24b6759206dee8aada682f | 2022-02-01T22:51:24.000Z | [
"pytorch",
"xglm",
"text-generation",
"transformers"
] | text-generation | false | KoboldAI | null | KoboldAI/fairseq-dense-6.7B | 390 | 1 | transformers | 2,576 | Entry not found |
microsoft/xprophetnet-large-wiki100-cased-xglue-ntg | c55500c832564c818a332d38597dc542b468d9e1 | 2021-09-06T12:32:22.000Z | [
"pytorch",
"xlm-prophetnet",
"text2text-generation",
"arxiv:2001.04063",
"arxiv:2004.01401",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | microsoft | null | microsoft/xprophetnet-large-wiki100-cased-xglue-ntg | 390 | null | transformers | 2,577 | ## xprophetnet-large-wiki100-cased-xglue-ntg
Cross-lingual version [ProphetNet](https://arxiv.org/abs/2001.04063), pretrained on [wiki100 xGLUE dataset](https://arxiv.org/abs/2004.01401) and finetuned on xGLUE cross-lingual News Titles Generation task.
ProphetNet is a new pre-trained language model for sequence-to-se... |
ynie/bart-large-snli_mnli_fever_anli_R1_R2_R3-nli | e9c498acc3d1c26ccabfc9ff96004e0790d16753 | 2020-10-17T02:00:14.000Z | [
"pytorch",
"bart",
"text-classification",
"transformers"
] | text-classification | false | ynie | null | ynie/bart-large-snli_mnli_fever_anli_R1_R2_R3-nli | 390 | 1 | transformers | 2,578 | Entry not found |
ridhoalattqas/xlrs-best-lm | c950a4d0cf1703936698d32107b00088c38c284b | 2022-06-06T09:13:28.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"id",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | ridhoalattqas | null | ridhoalattqas/xlrs-best-lm | 390 | 1 | transformers | 2,579 | ---
language: id
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Indonesian by Ridho
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
... |
flexudy/t5-small-wav2vec2-grammar-fixer | 5b4eca6292599a69adaa3a7b74435757f1d918a6 | 2021-02-16T01:56:40.000Z | [
"pytorch",
"tf"
] | null | false | flexudy | null | flexudy/t5-small-wav2vec2-grammar-fixer | 389 | 10 | null | 2,580 | # flexudy-pipe-question-generation-v2
After transcribing your audio with Wav2Vec2, you might be interested in a post processor.
All paragraphs had at most 128 tokens (separated by white spaces)
```python
from transformers import T5Tokenizer, T5ForConditionalGeneration
model_name = "flexudy/t5-small-wav2vec2-grammar-... |
brianveebee/DialoGPT-medium-bender | 78fcb5c5976dda427a9a4e1639f7e754bee63fb7 | 2022-07-10T00:01:21.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | brianveebee | null | brianveebee/DialoGPT-medium-bender | 389 | null | transformers | 2,581 | ---
tags:
- conversational
---
# Bender DialoGPT Model |
howey/roberta-large-mnli | fa26dd2471eee9cdb8ba8b179f21d26527104bee | 2021-06-03T14:21:19.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | howey | null | howey/roberta-large-mnli | 388 | null | transformers | 2,582 | Entry not found |
tosin/dialogpt_mwoz | e98e1e0c3b7661816187ddc5a9fd3b97f30db2d3 | 2021-12-02T09:32:03.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:multi_woz_v22",
"arxiv:2110.06273",
"transformers",
"conversational",
"license:cc-by-4.0"
] | conversational | false | tosin | null | tosin/dialogpt_mwoz | 388 | 2 | transformers | 2,583 | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
language:
- en
license: cc-by-4.0
tags:
- conversational
- transformers
datasets:
- multi_woz_v22
metrics:
- perplexity
widget:
- text: "I would like to have breakfast."
---
## DialoGPT_MWOZ
This is a fine-tuned model of DialoGPT (medium) on the Mult... |
bionlp/bluebert_pubmed_uncased_L-24_H-1024_A-16 | d9bd2536b238ea27b08fb502dc8586933c160453 | 2021-09-24T07:46:55.000Z | [
"pytorch",
"jax",
"en",
"dataset:PubMed",
"transformers",
"bert",
"bluebert",
"license:cc0-1.0"
] | null | false | bionlp | null | bionlp/bluebert_pubmed_uncased_L-24_H-1024_A-16 | 387 | null | transformers | 2,584 | ---
language:
- en
tags:
- bert
- bluebert
license: cc0-1.0
datasets:
- PubMed
---
# BlueBert-Base, Uncased, PubMed
## Model description
A BERT model pre-trained on PubMed abstracts.
## Intended uses & limitations
#### How to use
Please see https://github.com/ncbi-nlp/bluebert
## Training data
We provide [pre... |
nateraw/vit-age-classifier | f5629497debbd1a543fa49e0a86cadd145d4947d | 2021-05-24T03:09:01.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:fairface",
"transformers"
] | image-classification | false | nateraw | null | nateraw/vit-age-classifier | 387 | 1 | transformers | 2,585 | ---
tags:
- image-classification
- pytorch
datasets:
- fairface
---
# ViT For Age Classification
A vision transformer finetuned to classify the age of a given person's face.
## Usage in Transformers
```python
import requests
from PIL import Image
from io import BytesIO
from transformers import ViTFeatureExtracto... |
persiannlp/mt5-large-parsinlu-opus-translation_fa_en | 6ddd645d763bf11573b8764db5a8c66ace5e3bd5 | 2021-09-23T16:20:17.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"machine-translation",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-large-parsinlu-opus-translation_fa_en | 387 | null | transformers | 2,586 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- machine-translation
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- sacrebleu
---
# Machine Translation (ترجمهی ماشینی)
This is an mT5-based model for machine translatio... |
snunlp/KR-FinBert | 9ccc6ae2a35c65ed7156da9dc1fc5311f69abc3e | 2022-04-28T05:06:40.000Z | [
"pytorch",
"bert",
"fill-mask",
"ko",
"transformers",
"autotrain_compatible"
] | fill-mask | false | snunlp | null | snunlp/KR-FinBert | 387 | null | transformers | 2,587 | ---
language:
- ko
---
# KR-FinBert & KR-FinBert-SC
Much progress has been made in the NLP (Natural Language Processing) field, with numerous studies showing that domain adaptation using small-scale corpus and fine-tuning with labeled data is effective for overall performance improvement.
we proposed KR-FinBert for... |
facebook/convnext-base-224-22k | d72d44edaee962fb299e85c445eab8c628f71973 | 2022-02-26T12:19:16.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-21k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-base-224-22k | 386 | null | transformers | 2,588 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-21k
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... |
wannaphong/thaigpt-next-125m | c4a0ee2b6006cdcdc397ac1b77fc368dfd2d4277 | 2021-06-30T17:34:39.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | wannaphong | null | wannaphong/thaigpt-next-125m | 386 | 2 | transformers | 2,589 | # Thai GPT Next
It is fine-tune the GPT-Neo model for Thai language.
GitHub: https://github.com/wannaphong/thaigpt-next
**Dataset for fine-tune this model**
- prachathai67k
- thaisum
- thai_toxicity_tweet
- wongnai reviews
- wisesight_sentiment
- TLC
- scb_mt_enth_2020 (Thai only)
- Thai wikipedia (date: 2021/06/20... |
Jeevesh8/goog_bert_ft_cola-4 | 9124463129de27e85076cf78d260d574dab42e9c | 2022-06-29T17:31:49.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Jeevesh8 | null | Jeevesh8/goog_bert_ft_cola-4 | 386 | null | transformers | 2,590 | Entry not found |
dsksd/bert-ko-small-minimal | aaf41aa807d3f753634696ee7bf82d126223ee7f | 2021-05-19T16:09:26.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | dsksd | null | dsksd/bert-ko-small-minimal | 385 | null | transformers | 2,591 | Entry not found |
peterchou/ernie-gram | c0f76855dbb2a2055d8d6a076b10398ff4ee170d | 2021-05-21T15:26:54.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | peterchou | null | peterchou/ernie-gram | 385 | null | transformers | 2,592 | Entry not found |
lgrobol/electra-minuscule-generator | 202bce1ff6f7e2ab920354319d735a2186606036 | 2022-01-02T18:50:39.000Z | [
"pytorch",
"electra",
"fill-mask",
"multilingual",
"transformers",
"testing",
"minuscule",
"license:cc0-1.0",
"autotrain_compatible"
] | fill-mask | false | lgrobol | null | lgrobol/electra-minuscule-generator | 384 | null | transformers | 2,593 | ---
language: multilingual
tags:
- electra
- testing
- minuscule
license: "cc0-1.0"
---
ELECTRA-minuscule-generator
===============================
A ridiculously small ELECTRA generator model for testing purposes.
**THIS MODEL HAS NOT BEEN TRAINED, DO NOT EXPECT ANYThING OF IT.**
|
FinanceInc/finbert_fls | 354b28047f9c46cc5d6503ecbbf9c40c272874f4 | 2022-07-22T17:41:31.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"transformers",
"financial-text-analysis",
"forward-looking-statement"
] | text-classification | false | FinanceInc | null | FinanceInc/finbert_fls | 384 | null | transformers | 2,594 | ---
language: "en"
tags:
- financial-text-analysis
- forward-looking-statement
widget:
- text: "We expect the age of our fleet to enhance availability and reliability due to reduced downtime for repairs. "
---
Forward-looking statements (FLS) inform investors of managers’ beliefs and opinions about firm's future event... |
Soumyajit1008/DialoGPT-small-harryPotterssen | b580c9bb2aee929622eeddbd2bec7821163e2408 | 2022-02-01T16:20:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Soumyajit1008 | null | Soumyajit1008/DialoGPT-small-harryPotterssen | 383 | null | transformers | 2,595 | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model |
lgrobol/electra-minuscule-discriminator | f3cec9a74ebc921b3cc5a83b814805043b617d13 | 2021-12-30T23:12:11.000Z | [
"pytorch",
"electra",
"token-classification",
"multilingual",
"transformers",
"testing",
"minuscule",
"license:cc0-1.0",
"autotrain_compatible"
] | token-classification | false | lgrobol | null | lgrobol/electra-minuscule-discriminator | 383 | null | transformers | 2,596 | ---
language: multilingual
thumbnail: "url to a thumbnail used in social sharing"
tags:
- electra
- testing
- minuscule
license: "cc0-1.0"
---
ELECTRA-minuscule-discriminator
===============================
A ridiculously small ELECTRA discriminator model for testing purposes.
**THIS MODEL HAS NOT BEEN TRAINE... |
patrickvonplaten/bert2bert_cnn_daily_mail | 60cef1a6c33d35ea07afb476b561ecc483df1d6f | 2022-06-25T17:06:49.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"en",
"dataset:cnn_dailymail",
"transformers",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | patrickvonplaten | null | patrickvonplaten/bert2bert_cnn_daily_mail | 383 | 1 | transformers | 2,597 | ---
language: en
license: apache-2.0
datasets:
- cnn_dailymail
tags:
- summarization
model-index:
- name: patrickvonplaten/bert2bert_cnn_daily_mail
results:
- task:
type: summarization
name: Summarization
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: t... |
ChrisVCB/DialoGPT-medium-ej | a98ccda2c32fa1c573c5cad2fba50c199767b0d7 | 2021-12-09T03:22:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ChrisVCB | null | ChrisVCB/DialoGPT-medium-ej | 381 | null | transformers | 2,598 | ---
tags:
- conversational
---
# Eddie Jones DialoGPT Model |
Helsinki-NLP/opus-mt-en-uk | f2466c290a224ec84b2fcccee9c2891c1ab887ca | 2021-09-09T21:40:28.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"uk",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-uk | 380 | 1 | transformers | 2,599 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-uk
* source languages: en
* target languages: uk
* OPUS readme: [en-uk](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-uk/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
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