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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
facebook/convnext-tiny-224 | 0d1c8dedaa107d4ae537c5b10e5cd0a8c865e84e | 2022-02-26T12:15:30.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-tiny-224 | 6,835 | 2 | transformers | 800 | ---
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... |
deepset/bert-small-mm_retrieval-table_encoder | d2068c03905e9406dd5c192aef839ce3b938fa1a | 2021-10-19T16:22:42.000Z | [
"pytorch",
"dpr",
"transformers"
] | null | false | deepset | null | deepset/bert-small-mm_retrieval-table_encoder | 6,829 | null | transformers | 801 | Entry not found |
Salesforce/codegen-16B-multi | f509e154f23d9017a9f7843ab36a844ef8d2b308 | 2022-06-28T17:53:24.000Z | [
"pytorch",
"codegen",
"text-generation",
"arxiv:2203.13474",
"transformers",
"license:bsd-3-clause"
] | text-generation | false | Salesforce | null | Salesforce/codegen-16B-multi | 6,827 | 2 | transformers | 802 | ---
license: bsd-3-clause
---
# CodeGen (CodeGen-Multi 16B)
## Model description
CodeGen is a family of autoregressive language models for **program synthesis** from the paper: [A Conversational Paradigm for Program Synthesis](https://arxiv.org/abs/2203.13474) by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan ... |
Helsinki-NLP/opus-mt-tc-big-en-pt | 6cd179c3a36b2aa259d58bc8c0dc33af3d8e4632 | 2022-06-01T13:03:26.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"pt",
"pt_br",
"transformers",
"translation",
"opus-mt-tc",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tc-big-en-pt | 6,749 | 1 | transformers | 803 | ---
language:
- en
- pt
- pt_br
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-en-pt
results:
- task:
name: Translation eng-por
type: translation
args: eng-por
dataset:
name: flores101-devtest
type: flores_101
args: eng por devtest
... |
ahotrod/albert_xxlargev1_squad2_512 | 291f0fa26d2c80d8a473b6116164a083d252b4fe | 2020-12-11T21:31:38.000Z | [
"pytorch",
"tf",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | ahotrod | null | ahotrod/albert_xxlargev1_squad2_512 | 6,734 | 2 | transformers | 804 | ## Albert xxlarge version 1 language model fine-tuned on SQuAD2.0
### (updated 30Sept2020) with the following results:
```
exact: 86.11134506864315
f1: 89.35371214945009
total': 11873
HasAns_exact': 83.56950067476383
HasAns_f1': 90.06353312254078
HasAns_total': 5928
NoAns_exact': 88.64592094196804
NoAns_f1': 88.6459... |
dbmdz/bert-base-french-europeana-cased | b895c3cf291f7bf4c15639078a6bee0b3e272c5b | 2021-09-13T21:03:24.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fr",
"transformers",
"historic french",
"license:mit"
] | null | false | dbmdz | null | dbmdz/bert-base-french-europeana-cased | 6,725 | 1 | transformers | 805 | ---
language: fr
license: mit
tags:
- "historic french"
---
# 🤗 + 📚 dbmdz BERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources French Europeana BERT models 🎉
# French Europeana BERT
We extracted all French texts using the `language` metadata attribute fro... |
tprincessazula/Dialog-GPT-small-KATARA-AVATAR | 9e7c17b7f5ef120e895120c49721f3a000e5a240 | 2022-01-05T13:46:24.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | tprincessazula | null | tprincessazula/Dialog-GPT-small-KATARA-AVATAR | 6,721 | 1 | transformers | 806 | ---
tags:
- conversational
---
#KATARA DialoGPT Model |
Grossmend/rudialogpt3_medium_based_on_gpt2 | a2f8ac89182e36e352ea921de30cf2b0e9b30b89 | 2021-08-02T13:43:25.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"ru",
"transformers",
"convAI",
"conversational"
] | conversational | false | Grossmend | null | Grossmend/rudialogpt3_medium_based_on_gpt2 | 6,685 | 8 | transformers | 807 | ---
language:
- ru
thumbnail:
tags:
- convAI
- conversational
---
DialoGPT on Russian language
Article on Habr: https://habr.com/ru/company/icl_services/blog/548244/
Git: https://github.com/Grossmend/DialoGPT
#### How to use
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
tok... |
EEE/DialoGPT-medium-brooke | 6c5ccd6420a957b3116bbd02f21ed4e5ae1ac59d | 2021-09-27T06:25:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | EEE | null | EEE/DialoGPT-medium-brooke | 6,684 | null | transformers | 808 | ---
tags:
- conversational
---
# Brooke DialoGPT Model |
PlanTL-GOB-ES/roberta-base-bne | f4cc2aff5eaa2e1ad5add20a740d8578c833574a | 2022-04-06T14:40:52.000Z | [
"pytorch",
"roberta",
"fill-mask",
"es",
"dataset:bne",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/roberta-base-bne | 6,640 | 8 | transformers | 809 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
datasets:
- "bne"
metrics:
- "ppl"
widget:
- text: "Este año las campanadas de La Sexta las presentará <mask>."
- text: "David Broncano es un presentador de La <mask>."
- text: "Gracias a los datos de la BNE se ha podido <... |
nvidia/mit-b3 | 3a0bee80ae595e8ae292ddd7b2dfe0845cda2161 | 2022-07-29T13:15:53.000Z | [
"pytorch",
"tf",
"segformer",
"image-classification",
"dataset:imagenet_1k",
"arxiv:2105.15203",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | nvidia | null | nvidia/mit-b3 | 6,618 | null | transformers | 810 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet_1k
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000002.jpg
exampl... |
AmbricJohnson5888/death | 68ca65a4f20454f7ea435dba297a0d959cd67183 | 2022-04-09T02:19:17.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | AmbricJohnson5888 | null | AmbricJohnson5888/death | 6,589 | null | transformers | 811 | ---
tags:
- conversational
---
#DEATH
#https://discord.gg/kNxBCv7DtK |
harshit345/xlsr-wav2vec-speech-emotion-recognition | 7fd191edd9a505af312467d6f00fede29cff0da1 | 2021-12-12T20:53:33.000Z | [
"pytorch",
"wav2vec2",
"en",
"dataset:aesdd",
"transformers",
"audio",
"audio-classification",
"speech",
"license:apache-2.0"
] | audio-classification | false | harshit345 | null | harshit345/xlsr-wav2vec-speech-emotion-recognition | 6,566 | 3 | transformers | 812 | ---
language: en
datasets:
- aesdd
tags:
- audio
- audio-classification
- speech
license: apache-2.0
---
~~~
# requirement packages
!pip install git+https://github.com/huggingface/datasets.git
!pip install git+https://github.com/huggingface/transformers.git
!pip install torchaudio
!pip install librosa
~~~
# prediction... |
cl-tohoku/bert-base-japanese-char-v2 | e17e40a15857ad47d63f6eb4cc9fb62c136d2301 | 2021-09-23T13:45:24.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ja",
"dataset:wikipedia",
"transformers",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | cl-tohoku | null | cl-tohoku/bert-base-japanese-char-v2 | 6,540 | 1 | transformers | 813 | ---
language: ja
license: cc-by-sa-4.0
datasets:
- wikipedia
widget:
- text: 東北大学で[MASK]の研究をしています。
---
# BERT base Japanese (character-level tokenization with whole word masking, jawiki-20200831)
This is a [BERT](https://github.com/google-research/bert) model pretrained on texts in the Japanese language.
This versio... |
hf-internal-testing/test_dynamic_model | 2efddce40dddaccd37bae208c3c7ca66dbedf68a | 2022-01-25T22:03:13.000Z | [
"pytorch",
"new-model",
"transformers"
] | null | false | hf-internal-testing | null | hf-internal-testing/test_dynamic_model | 6,540 | null | transformers | 814 | Entry not found |
Rostlab/prot_t5_xl_half_uniref50-enc | 2646ade9d44b7620ceac59797b2d9efd3341da37 | 2022-06-29T08:22:26.000Z | [
"pytorch",
"t5",
"protein",
"dataset:UniRef50",
"transformers",
"protein language model"
] | null | false | Rostlab | null | Rostlab/prot_t5_xl_half_uniref50-enc | 6,489 | null | transformers | 815 | ---
language: protein
tags:
- protein language model
datasets:
- UniRef50
---
# Encoder only ProtT5-XL-UniRef50, half-precision model
An encoder-only, half-precision version of the [ProtT5-XL-UniRef50](https://huggingface.co/Rostlab/prot_t5_xl_uniref50) model. The original model and it's pretraining were introduced i... |
sentence-transformers/distilroberta-base-paraphrase-v1 | 0191e446424b49506ba016264788b49bb7b11eb9 | 2022-06-15T21:53:03.000Z | [
"pytorch",
"tf",
"roberta",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/distilroberta-base-paraphrase-v1 | 6,468 | null | sentence-transformers | 816 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/distilroberta-base-paraphrase-v1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensi... |
hakurei/lit-6B | cc2e78adb62590cb2889d338d46f8cf1ef396453 | 2021-11-08T23:02:41.000Z | [
"pytorch",
"gptj",
"text-generation",
"en",
"transformers",
"causal-lm",
"license:mit"
] | text-generation | false | hakurei | null | hakurei/lit-6B | 6,455 | 6 | transformers | 817 | ---
language:
- en
tags:
- pytorch
- causal-lm
license: mit
---
# Lit-6B - A Large Fine-tuned Model For Fictional Storytelling
Lit-6B is a GPT-J 6B model fine-tuned on 2GB of a diverse range of light novels, erotica, and annotated literature for the purpose of generating novel-like fictional text.
## Model Descrip... |
Helsinki-NLP/opus-mt-lv-en | 3b019339e88ac4f79044be45cfa75ff5fedbceea | 2021-09-10T13:57:07.000Z | [
"pytorch",
"marian",
"text2text-generation",
"lv",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-lv-en | 6,444 | null | transformers | 818 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-lv-en
* source languages: lv
* target languages: en
* OPUS readme: [lv-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/lv-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
flair/upos-english-fast | 352fcf521848b438afba2fdb6846e18dbb3ad514 | 2021-03-02T22:21:02.000Z | [
"pytorch",
"en",
"dataset:ontonotes",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | flair | null | flair/upos-english-fast | 6,436 | 2 | flair | 819 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- ontonotes
widget:
- text: "I love Berlin."
---
## English Universal Part-of-Speech Tagging in Flair (fast model)
This is the fast universal part-of-speech tagging model for English that ships with [Flair](https://github.com/flai... |
sshleifer/tiny-ctrl | d76c849d54c665ccfd33b8aa501b17531289cae9 | 2020-05-13T23:21:48.000Z | [
"pytorch",
"tf",
"ctrl",
"text-generation",
"transformers"
] | text-generation | false | sshleifer | null | sshleifer/tiny-ctrl | 6,417 | null | transformers | 820 | Entry not found |
camembert/camembert-base | e12767c19b74b1efc75b0af07bbde51ddd26b529 | 2022-06-17T23:06:40.000Z | [
"pytorch",
"camembert",
"fill-mask",
"fr",
"arxiv:1911.03894",
"transformers",
"autotrain_compatible"
] | fill-mask | false | camembert | null | camembert/camembert-base | 6,388 | null | transformers | 821 | ---
language: fr
---
# CamemBERT: a Tasty French Language Model
## Introduction
[CamemBERT](https://arxiv.org/abs/1911.03894) is a state-of-the-art language model for French based on the RoBERTa model.
It is now available on Hugging Face in 6 different versions with varying number of parameters, amount of pretrain... |
hf-internal-testing/tiny-random-speech-encoder-decoder | 880a6041222f5297adfceb3debd1a955d1c48ba5 | 2021-12-24T15:13:44.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | hf-internal-testing | null | hf-internal-testing/tiny-random-speech-encoder-decoder | 6,373 | null | transformers | 822 | Entry not found |
hiiamsid/sentence_similarity_spanish_es | 2817cf8566982a08b43bc4d6f74924010bc56f65 | 2021-10-18T03:52:32.000Z | [
"pytorch",
"bert",
"feature-extraction",
"es",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | hiiamsid | null | hiiamsid/sentence_similarity_spanish_es | 6,371 | 4 | sentence-transformers | 823 | ---
pipeline_tag: sentence-similarity
language:
- es
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# hiiamsid/sentence_similarity_spanish_es
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector sp... |
google/vit-base-patch32-224-in21k | ebb34016d84eb82beee2f88d5ae21a1f08a8ca88 | 2022-01-12T08:06:34.000Z | [
"pytorch",
"tf",
"jax",
"vit",
"feature-extraction",
"dataset:imagenet-21k",
"arxiv:2010.11929",
"arxiv:2006.03677",
"transformers",
"vision",
"license:apache-2.0"
] | feature-extraction | false | google | null | google/vit-base-patch32-224-in21k | 6,344 | null | transformers | 824 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet-21k
inference: false
---
# Vision Transformer (base-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. It was introduced in the paper [An Image is Worth 16x16 Words: Transformer... |
Salesforce/bart-large-xsum-samsum | bf8a8779c158901df223516a72b9efaa887ed1df | 2021-06-09T19:36:02.000Z | [
"pytorch",
"tf",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Salesforce | null | Salesforce/bart-large-xsum-samsum | 6,327 | 4 | transformers | 825 | Entry not found |
anferico/bert-for-patents | d1a25632e9c586399068a2f139d5664306b32ad8 | 2022-06-23T19:22:35.000Z | [
"pytorch",
"tf",
"fill-mask",
"en",
"transformers",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | anferico | null | anferico/bert-for-patents | 6,311 | 24 | transformers | 826 | ---
language:
- en
tags:
- masked-lm
- pytorch
pipeline-tag: "fill-mask"
mask-token: "[MASK]"
widget:
- text: "The present [MASK] provides a torque sensor that is small and highly rigid and for which high production efficiency is possible."
- text: "The present invention relates to [MASK] accessories and pertains pa... |
nvidia/mit-b0 | 698892efdcedeeb02bce6a40d3f4830e469bbff9 | 2022-07-29T13:15:48.000Z | [
"pytorch",
"tf",
"segformer",
"image-classification",
"dataset:imagenet_1k",
"arxiv:2105.15203",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | nvidia | null | nvidia/mit-b0 | 6,248 | 2 | transformers | 827 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet_1k
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000002.jpg
exampl... |
flair/chunk-english | ade3849ae09b28854c9bad0a6ec4028ba547bae2 | 2021-03-02T22:00:37.000Z | [
"pytorch",
"en",
"dataset:conll2000",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | flair | null | flair/chunk-english | 6,206 | 4 | flair | 828 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- conll2000
widget:
- text: "The happy man has been eating at the diner"
---
## English Chunking in Flair (default model)
This is the standard phrase chunking model for English that ships with [Flair](https://github.com/flairNLP/f... |
facebook/blenderbot-90M | 3e5344952a74d2017762fa8428c45edd07f3dea7 | 2021-03-12T06:17:25.000Z | [
"pytorch",
"blenderbot-small",
"text2text-generation",
"en",
"dataset:blended_skill_talk",
"arxiv:1907.06616",
"transformers",
"convAI",
"conversational",
"facebook",
"license:apache-2.0",
"autotrain_compatible"
] | conversational | false | facebook | null | facebook/blenderbot-90M | 6,163 | null | transformers | 829 | ---
language:
- en
thumbnail:
tags:
- convAI
- conversational
- facebook
license: apache-2.0
datasets:
- blended_skill_talk
metrics:
- perplexity
---
# 🚨🚨**IMPORTANT**🚨🚨
**This model is deprecated! Please use the identical model** **https://huggingface.co/facebook/blenderbot_small-90M instead**
## Model descrip... |
Peltarion/xlm-roberta-longformer-base-4096 | c2e164abd333ebd242de4178ea18c1260e00d330 | 2022-03-30T09:23:58.000Z | [
"pytorch",
"xlm-roberta",
"fill-mask",
"multilingual",
"dataset:wikitext",
"transformers",
"longformer",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Peltarion | null | Peltarion/xlm-roberta-longformer-base-4096 | 6,159 | 2 | transformers | 830 | ---
tags:
- longformer
language: multilingual
license: apache-2.0
datasets:
- wikitext
---
## XLM-R Longformer Model
XLM-R Longformer is a XLM-R model, that has been extended to allow sequence lengths up to 4096 tokens, instead of the regular 512. The model was pre-trained from the XLM-RoBERTa checkpoint using the ... |
DeepPavlov/bert-base-cased-conversational | 5415204d80daf12299c85dfddec5f5a7fc7b620a | 2021-11-08T13:07:31.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"en",
"transformers"
] | feature-extraction | false | DeepPavlov | null | DeepPavlov/bert-base-cased-conversational | 6,152 | 3 | transformers | 831 | ---
language: en
---
# bert-base-cased-conversational
Conversational BERT \(English, cased, 12‑layer, 768‑hidden, 12‑heads, 110M parameters\) was trained on the English part of Twitter, Reddit, DailyDialogues\[1\], OpenSubtitles\[2\], Debates\[3\], Blogs\[4\], Facebook News Comments. We used this training data to bui... |
fnlp/bart-large-chinese | b47be247db39e74f5383784524c68bfddf0aa496 | 2021-10-29T05:19:42.000Z | [
"pytorch",
"bart",
"feature-extraction",
"zh",
"arxiv:2109.05729",
"transformers",
"text2text-generation",
"Chinese",
"seq2seq"
] | feature-extraction | false | fnlp | null | fnlp/bart-large-chinese | 6,147 | 14 | transformers | 832 | ---
tags:
- text2text-generation
- Chinese
- seq2seq
language: zh
---
# Chinese BART-Large
## Model description
This is an implementation of Chinese BART-Large.
[**CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation**](https://arxiv.org/pdf/2109.05729.pdf)
Yunfan Shao, ... |
flair/ner-french | 84166b7e2ebffceaf9807a7eaf90ec07f7cc01a4 | 2021-02-26T15:43:57.000Z | [
"pytorch",
"fr",
"dataset:conll2003",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | flair | null | flair/ner-french | 6,146 | 2 | flair | 833 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: fr
datasets:
- conll2003
widget:
- text: "George Washington est allé à Washington"
---
## French NER in Flair (default model)
This is the standard 4-class NER model for French that ships with [Flair](https://github.com/flairNLP/flair/).
F1-Sc... |
facebook/opt-13b | 45d913414643f29e9273a362ef881109c36b72a5 | 2022-06-24T05:21:44.000Z | [
"pytorch",
"tf",
"jax",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"arxiv:2005.14165",
"transformers",
"license:other"
] | text-generation | false | facebook | null | facebook/opt-13b | 6,121 | 9 | transformers | 834 | ---
language: en
inference: false
tags:
- opt
- text-generation
license: other
commercial: false
---
# OPT : Open Pre-trained Transformer Language Models
OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://g... |
MilaNLProc/xlm-emo-t | cbec0894eb5035a2a513cd7e786a4d7772cfe45b | 2022-06-08T13:02:56.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"multilingual",
"arxiv:2104.12250",
"transformers",
"emotion",
"emotion-analysis",
"license:mit"
] | text-classification | false | MilaNLProc | null | MilaNLProc/xlm-emo-t | 6,097 | 1 | transformers | 835 | ---
language: multilingual
license: mit
tags:
- emotion
- emotion-analysis
- multilingual
widget:
- text: "Guarda! ci sono dei bellissimi capibara!"
example_title: "Emotion Classification 1"
- text: "Sei una testa di cazzo!!"
example_title: "Emotion Classification 2"
- text: "Quelle bonne nouvelle!"
example_titl... |
laxya007/gpt2_bd2_systemanalysis | f190dfa6ad8c5077f45c04d13a5c57c9e28c4979 | 2022-07-05T16:43:36.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | laxya007 | null | laxya007/gpt2_bd2_systemanalysis | 6,091 | null | transformers | 836 | Entry not found |
bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12 | c656dbe1fc4d6c7771d93bcaff21b2e7984f64c8 | 2021-09-24T07:46:11.000Z | [
"pytorch",
"jax",
"en",
"dataset:PubMed",
"dataset:MIMIC-III",
"transformers",
"bert",
"bluebert",
"license:cc0-1.0"
] | null | false | bionlp | null | bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12 | 6,085 | 3 | transformers | 837 | ---
language:
- en
tags:
- bert
- bluebert
license: cc0-1.0
datasets:
- PubMed
- MIMIC-III
---
# BlueBert-Base, Uncased, PubMed and MIMIC-III
## Model description
A BERT model pre-trained on PubMed abstracts and clinical notes ([MIMIC-III](https://mimic.physionet.org/)).
## Intended uses & limitations
#### How t... |
sonoisa/sentence-bert-base-ja-mean-tokens-v2 | a230680fdb31ed495808f08e2d700361dc982542 | 2021-12-26T08:33:30.000Z | [
"pytorch",
"bert",
"feature-extraction",
"ja",
"sentence-transformers",
"sentence-bert",
"sentence-similarity",
"license:cc-by-sa-4.0"
] | feature-extraction | false | sonoisa | null | sonoisa/sentence-bert-base-ja-mean-tokens-v2 | 6,080 | 4 | sentence-transformers | 838 | ---
language: ja
license: cc-by-sa-4.0
tags:
- sentence-transformers
- sentence-bert
- feature-extraction
- sentence-similarity
---
**※重要: 2021/12/26 モデルを修正しました。誤って精度が低いモデルを公開していたため、精度が高いモデルに差し替えました。**
This is a Japanese sentence-BERT model.
日本語用Sentence-BERTモデル（バージョン2）です。
[バージョン1](https://huggingface.co/sonoisa/s... |
dmis-lab/biobert-large-cased-v1.1 | c6775648fdc33f369c4342679bcf0f2691e08b3c | 2020-10-14T06:19:39.000Z | [
"pytorch",
"transformers"
] | null | false | dmis-lab | null | dmis-lab/biobert-large-cased-v1.1 | 6,013 | 1 | transformers | 839 | Entry not found |
ckiplab/bert-base-chinese-pos | c3f173670d4793f00ce5d23381cbeffa17e4e197 | 2022-05-10T03:28:12.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"zh",
"transformers",
"license:gpl-3.0",
"autotrain_compatible"
] | token-classification | false | ckiplab | null | ckiplab/bert-base-chinese-pos | 6,011 | 2 | transformers | 840 | ---
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- token-classification
- bert
- zh
license: gpl-3.0
---
# CKIP BERT Base Chinese
This project provides traditional Chinese transformers models (including ALBERT, BERT, GPT2) and NLP tools (including word segment... |
Rostlab/prot_t5_xl_bfd | 7ae1d5c1d148d6c65c7e294cc72807e5b454fdb7 | 2020-12-11T21:30:13.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"protein",
"dataset:BFD",
"transformers",
"protein language model",
"autotrain_compatible"
] | text2text-generation | false | Rostlab | null | Rostlab/prot_t5_xl_bfd | 5,994 | 2 | transformers | 841 | ---
language: protein
tags:
- protein language model
datasets:
- BFD
---
# ProtT5-XL-BFD model
Pretrained model on protein sequences using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://doi.org/10.1101/2020.07.12.199554) and first released in
[this repository](https://github.com... |
blanchefort/rubert-base-cased-sentiment | 1dfb5bcf1904a12eb157a0dfaf06029e606ce7c7 | 2021-05-19T13:05:55.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"ru",
"transformers",
"sentiment"
] | text-classification | false | blanchefort | null | blanchefort/rubert-base-cased-sentiment | 5,933 | 2 | transformers | 842 | ---
language:
- ru
tags:
- sentiment
- text-classification
---
# RuBERT for Sentiment Analysis
Short Russian texts sentiment classification
This is a [DeepPavlov/rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversational) model trained on aggregated corpus of 351.797 texts.
... |
hfl/rbt6 | 460e5cea82f393f75495db07da8055a957b53a2c | 2021-05-19T19:22:02.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"arxiv:1906.08101",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | hfl | null | hfl/rbt6 | 5,928 | 2 | transformers | 843 | ---
language:
- zh
tags:
- bert
license: "apache-2.0"
---
# This is a re-trained 6-layer RoBERTa-wwm-ext model.
## Chinese BERT with Whole Word Masking
For further accelerating Chinese natural language processing, we provide **Chinese pre-trained BERT with Whole Word Masking**.
**[Pre-Training with Whole Word Maski... |
flair/ner-german | a68cf20d7900104ff560f9bfbdfddb24f9c37282 | 2021-02-26T15:38:47.000Z | [
"pytorch",
"de",
"dataset:conll2003",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | flair | null | flair/ner-german | 5,919 | 4 | flair | 844 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: de
datasets:
- conll2003
widget:
- text: "George Washington ging nach Washington"
---
## German NER in Flair (default model)
This is the standard 4-class NER model for German that ships with [Flair](https://github.com/flairNLP/flair/).
F1-Sco... |
allenai/unifiedqa-t5-3b | 2f8ea967707edd861f92957b4f7f90d96175e7c2 | 2020-11-13T11:54:17.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-t5-3b | 5,897 | null | transformers | 845 | Entry not found |
shibing624/macbert4csc-base-chinese | a3383e26cc84638663a8681b141a6fdeabf09b72 | 2022-01-29T04:00:02.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | shibing624 | null | shibing624/macbert4csc-base-chinese | 5,854 | 16 | transformers | 846 | ---
language:
- zh
tags:
- bert
- pytorch
- zh
license: "apache-2.0"
---
# MacBERT for Chinese Spelling Correction(macbert4csc) Model
中文拼写纠错模型
`macbert4csc-base-chinese` evaluate SIGHAN2015 test data：
- Char Level: precision:0.9372, recall:0.8640, f1:0.8991
- Sentence Level: precision:0.8264, recall:0.7366, f1:... |
DB13067/Peterbot | 8562a504120603feadd5d9c676ea3e3f8c5ff72b | 2022-03-14T13:51:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | DB13067 | null | DB13067/Peterbot | 5,853 | null | transformers | 847 | ---
tags:
- conversational
---
# Peter from Your Boyfriend Game.
|
obi/deid_bert_i2b2 | 8ceb8983df9f0bf75d8c4bac345e157d80b4a5f7 | 2022-02-16T14:41:21.000Z | [
"pytorch",
"bert",
"token-classification",
"english",
"dataset:I2B2",
"arxiv:1904.03323",
"transformers",
"deidentification",
"medical notes",
"ehr",
"phi",
"license:mit",
"autotrain_compatible"
] | token-classification | false | obi | null | obi/deid_bert_i2b2 | 5,835 | 1 | transformers | 848 | ---
language:
- english
thumbnail: "https://www.onebraveidea.org/wp-content/uploads/2019/07/OBI-Logo-Website.png"
tags:
- deidentification
- medical notes
- ehr
- phi
datasets:
- I2B2
metrics:
- F1
- Recall
- AUC
widget:
- text: "Physician Discharge Summary Admit date: 10/12/1982 Discharge date: 10/22/1982 Patient In... |
allenai/wmt19-de-en-6-6-base | a9ec1968c8c3962f0f85f9f38ee4b8093ce84f24 | 2020-12-11T21:33:27.000Z | [
"pytorch",
"fsmt",
"text2text-generation",
"de",
"en",
"dataset:wmt19",
"arxiv:2006.10369",
"transformers",
"translation",
"wmt19",
"allenai",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | allenai | null | allenai/wmt19-de-en-6-6-base | 5,811 | null | transformers | 849 |
---
language:
- de
- en
thumbnail:
tags:
- translation
- wmt19
- allenai
license: apache-2.0
datasets:
- wmt19
metrics:
- bleu
---
# FSMT
## Model description
This is a ported version of fairseq-based [wmt19 transformer](https://github.com/jungokasai/deep-shallow/) for de-en.
For more details, please, see [Deep E... |
mrm8488/distill-bert-base-spanish-wwm-cased-finetuned-spa-squad2-es | a8842522e00a16b382c875ecb2da2dd8cf7cf5b6 | 2022-03-30T20:37:58.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"es",
"transformers",
"autotrain_compatible"
] | question-answering | false | mrm8488 | null | mrm8488/distill-bert-base-spanish-wwm-cased-finetuned-spa-squad2-es | 5,802 | 12 | transformers | 850 | ---
language: es
thumbnail: https://i.imgur.com/jgBdimh.png
---
# BETO (Spanish BERT) + Spanish SQuAD2.0 + distillation using 'bert-base-multilingual-cased' as teacher
This model is a fine-tuned on [SQuAD-es-v2.0](https://github.com/ccasimiro88/TranslateAlignRetrieve) and **distilled** version of [BETO](https://githu... |
avichr/heBERT | 01566c04aa226325662d5054331458e14ef3ede1 | 2022-04-15T09:36:09.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible"
] | fill-mask | false | avichr | null | avichr/heBERT | 5,778 | 1 | transformers | 851 | ## HeBERT: Pre-trained BERT for Polarity Analysis and Emotion Recognition
HeBERT is a Hebrew pretrained language model. It is based on Google's BERT architecture and it is BERT-Base config [(Devlin et al. 2018)](https://arxiv.org/abs/1810.04805). <br>
### HeBert was trained on three dataset:
1. A Hebrew version of OS... |
Helsinki-NLP/opus-mt-uk-en | d6c1e62ab5c03e34a3d118382be7a27b704241f0 | 2021-09-11T10:51:14.000Z | [
"pytorch",
"marian",
"text2text-generation",
"uk",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-uk-en | 5,763 | null | transformers | 852 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-uk-en
* source languages: uk
* target languages: en
* OPUS readme: [uk-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/uk-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
remotejob/gradientclassification_v0 | a9178cb4e1f714eb99b5076f363a5f4ddab726c6 | 2021-11-12T22:55:12.000Z | [
"pytorch",
"rust",
"bert",
"text-classification",
"transformers"
] | text-classification | false | remotejob | null | remotejob/gradientclassification_v0 | 5,761 | null | transformers | 853 | Entry not found |
amberoad/bert-multilingual-passage-reranking-msmarco | ed2597214a09ac6a3095b64c1ec49309daab5d9c | 2021-09-21T16:00:16.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"multilingual",
"dataset:msmarco",
"arxiv:1901.04085",
"transformers",
"msmarco",
"passage reranking",
"license:apache-2.0"
] | text-classification | false | amberoad | null | amberoad/bert-multilingual-passage-reranking-msmarco | 5,754 | 6 | transformers | 854 | ---
language: multilingual
thumbnail: https://amberoad.de/images/logo_text.png
tags:
- msmarco
- multilingual
- passage reranking
license: apache-2.0
datasets:
- msmarco
metrics:
- MRR
widget:
- query: What is a corporation?
passage: A company is incorporated in a specific nation, often within the bounds
of a sma... |
vblagoje/dpr-question_encoder-single-lfqa-wiki | bf06f6e217a69a4c1421c3eab66bf16a503e28f5 | 2022-03-11T10:11:16.000Z | [
"pytorch",
"dpr",
"feature-extraction",
"en",
"dataset:vblagoje/lfqa",
"transformers",
"license:mit"
] | feature-extraction | false | vblagoje | null | vblagoje/dpr-question_encoder-single-lfqa-wiki | 5,752 | null | transformers | 855 | ---
language: en
datasets:
- vblagoje/lfqa
license: mit
---
## Introduction
The question encoder model based on [DPRQuestionEncoder](https://huggingface.co/docs/transformers/master/en/model_doc/dpr#transformers.DPRQuestionEncoder) architecture. It uses the transformer's pooler outputs as question representations. See ... |
AmbricJohnson5888/claura | bb46422b9136a2fc1217cd6debdf362e49f26743 | 2022-04-09T04:18:57.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | AmbricJohnson5888 | null | AmbricJohnson5888/claura | 5,741 | null | transformers | 856 | ---
tags:
- conversational
---
#claura #https://discord.gg/kNxBCv7DtK |
cahya/bert-base-indonesian-NER | 4d361d082a907c349cc9dc53e08a75be21673a7c | 2021-05-19T13:39:48.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | cahya | null | cahya/bert-base-indonesian-NER | 5,724 | null | transformers | 857 | Entry not found |
microsoft/DialogRPT-updown | afe1247fd7e1b3abea28a52ea72db4ce1c8d2186 | 2021-05-23T09:19:13.000Z | [
"pytorch",
"gpt2",
"text-classification",
"arxiv:2009.06978",
"transformers"
] | text-classification | false | microsoft | null | microsoft/DialogRPT-updown | 5,709 | 3 | transformers | 858 | # Demo
Please try this [➤➤➤ Colab Notebook Demo (click me!)](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)
| Context | Response | `updown` score |
| :------ | :------- | :------------: |
| I love NLP! | Here’s a free textbook (URL) in case anyone needs it. | 0.613 |
| I... |
mrm8488/bert-spanish-cased-finetuned-ner | b11721d41d9e948da32fcdabeeef4fb0f3ebcdf7 | 2021-05-20T00:35:25.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"es",
"transformers",
"autotrain_compatible"
] | token-classification | false | mrm8488 | null | mrm8488/bert-spanish-cased-finetuned-ner | 5,705 | 1 | transformers | 859 | ---
language: es
thumbnail: https://i.imgur.com/jgBdimh.png
---
# Spanish BERT (BETO) + NER
This model is a fine-tuned on [NER-C](https://www.kaggle.com/nltkdata/conll-corpora) version of the Spanish BERT cased [(BETO)](https://github.com/dccuchile/beto) for **NER** downstream task.
## Details of the downstream task... |
stas/tiny-wmt19-en-de | 18ca8fc156edb91968dd4d70e33fbe5989d04368 | 2021-05-03T01:48:44.000Z | [
"pytorch",
"fsmt",
"text2text-generation",
"en",
"de",
"dataset:wmt19",
"transformers",
"wmt19",
"testing",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | stas | null | stas/tiny-wmt19-en-de | 5,674 | null | transformers | 860 | ---
language:
- en
- de
thumbnail:
tags:
- wmt19
- testing
license: apache-2.0
datasets:
- wmt19
metrics:
- bleu
---
# Tiny FSMT en-de
This is a tiny model that is used in the `transformers` test suite. It doesn't do anything useful, other than testing that `modeling_fsmt.py` is functional.
Do not try to use it for ... |
ktrapeznikov/albert-xlarge-v2-squad-v2 | fb1e05445e376bdb883e8d4f6696a0acaf62e0ae | 2020-12-11T21:48:41.000Z | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | ktrapeznikov | null | ktrapeznikov/albert-xlarge-v2-squad-v2 | 5,672 | 1 | transformers | 861 | ### Model
**[`albert-xlarge-v2`](https://huggingface.co/albert-xlarge-v2)** fine-tuned on **[`SQuAD V2`](https://rajpurkar.github.io/SQuAD-explorer/)** using **[`run_squad.py`](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_squad.py)**
### Training Parameters
Trained on 4 NVIDI... |
yiyanghkust/finbert-pretrain | 5b0dae12fea8ca5b3f256267ebe4e21786f3cfe5 | 2021-09-15T01:27:00.000Z | [
"pytorch",
"fill-mask",
"arxiv:2006.08097",
"transformers",
"autotrain_compatible"
] | fill-mask | false | yiyanghkust | null | yiyanghkust/finbert-pretrain | 5,672 | 6 | transformers | 862 | `FinBERT` is a BERT model pre-trained on financial communication text. The purpose is to enhance financial NLP research and practice. It is trained on the following three financial communication corpus. The total corpora size is 4.9B tokens.
- Corporate Reports 10-K & 10-Q: 2.5B tokens
- Earnings Call Transcripts: 1.3... |
cointegrated/roberta-large-cola-krishna2020 | 8386814a366a824280df5690a810fe038d7a270b | 2021-11-11T05:13:52.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:2010.05700",
"transformers"
] | text-classification | false | cointegrated | null | cointegrated/roberta-large-cola-krishna2020 | 5,642 | 1 | transformers | 863 | This is a RoBERTa-large classifier trained on the CoLA corpus [Warstadt et al., 2019](https://www.mitpressjournals.org/doi/pdf/10.1162/tacl_a_00290),
which contains sentences paired with grammatical acceptability judgments. The model can be used to evaluate fluency of machine-generated English sentences, e.g. for eval... |
vblagoje/dpr-ctx_encoder-single-lfqa-wiki | 8b412d76cb82502888936bce86775a81f454c398 | 2022-02-14T15:51:28.000Z | [
"pytorch",
"dpr",
"en",
"dataset:vblagoje/lfqa",
"transformers",
"license:mit"
] | null | false | vblagoje | null | vblagoje/dpr-ctx_encoder-single-lfqa-wiki | 5,617 | 1 | transformers | 864 | ---
language: en
datasets:
- vblagoje/lfqa
license: mit
---
## Introduction
The context/passage encoder model based on [DPRContextEncoder](https://huggingface.co/docs/transformers/master/en/model_doc/dpr#transformers.DPRContextEncoder) architecture. It uses the transformer's pooler outputs as context/passage represent... |
Helsinki-NLP/opus-mt-en-ar | 12f7bc254b7e475b6377f440d488063d7fb51571 | 2021-02-28T14:15:11.000Z | [
"pytorch",
"rust",
"marian",
"text2text-generation",
"en",
"ar",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ar | 5,575 | 5 | transformers | 865 | ---
language:
- en
- ar
tags:
- translation
license: apache-2.0
---
### eng-ara
* source group: English
* target group: Arabic
* OPUS readme: [eng-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ara/README.md)
* model: transformer
* source language(s): eng
* target language(s): a... |
allenai/led-large-16384-arxiv | 6d566f57e58195c1810dd8497ccf7f015409a1a9 | 2021-01-12T23:14:11.000Z | [
"pytorch",
"tf",
"led",
"text2text-generation",
"en",
"dataset:scientific_papers",
"arxiv:2004.05150",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/led-large-16384-arxiv | 5,570 | 4 | transformers | 866 | ---
language: en
datasets:
- scientific_papers
license: apache-2.0
---
## Introduction
[Allenai's Longformer Encoder-Decoder (LED)](https://github.com/allenai/longformer#longformer).
This is the official *led-large-16384* checkpoint that is fine-tuned on the arXiv dataset.*led-large-16384-arxiv* is the official f... |
luhua/chinese_pretrain_mrc_roberta_wwm_ext_large | 71a61139397cbb5fd773d8b8b72282a3387ff130 | 2021-06-12T02:53:16.000Z | [
"pytorch",
"bert",
"question-answering",
"zh",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | luhua | null | luhua/chinese_pretrain_mrc_roberta_wwm_ext_large | 5,543 | 15 | transformers | 867 | ---
language:
- zh
license: "apache-2.0"
---
## Chinese MRC roberta_wwm_ext_large
* 使用大量中文MRC数据训练的roberta_wwm_ext_large模型，详情可查看：https://github.com/basketballandlearn/MRC_Competition_Dureader
* 此库发布的再训练模型，在 阅读理解/分类 等任务上均有大幅提高<br/>
（已有多位小伙伴在Dureader-2021等多个比赛中取得**top5**的成绩😁）
| 模型/数据集 |... |
facebook/incoder-1B | 01f46041ac45a5a1ac9a60875189c15209d2fee9 | 2022-05-31T16:56:08.000Z | [
"pytorch",
"xglm",
"text-generation",
"arxiv:2204.05999",
"transformers",
"code",
"python",
"javascript",
"license:cc-by-nc-4.0"
] | text-generation | false | facebook | null | facebook/incoder-1B | 5,521 | 12 | transformers | 868 | ---
license: "cc-by-nc-4.0"
tags:
- code
- python
- javascript
---
# InCoder 1B
A 1B parameter decoder-only Transformer model trained on code using a causal-masked objective, which allows inserting/infilling code as well as standard left-to-right generation.
The model was trained on public open-source repositories w... |
nielsr/layoutlmv2-finetuned-funsd | 35c7fa55e4df524ded1485d406ef540b4b4320db | 2021-09-17T08:24:35.000Z | [
"pytorch",
"tensorboard",
"layoutlmv2",
"token-classification",
"dataset:funsd",
"transformers",
"generated_from_trainer",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | nielsr | null | nielsr/layoutlmv2-finetuned-funsd | 5,515 | 8 | transformers | 869 | ---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- funsd
model_index:
- name: layoutlmv2-finetuned-funsd
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: funsd
type: funsd
args: funsd
---
<!-- This model card has been generate... |
avichr/heBERT_sentiment_analysis | 022c0d00fc26288c25c0b9f5389d7f0991f93de2 | 2021-12-31T16:08:22.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"arxiv:1810.04805",
"transformers"
] | text-classification | false | avichr | null | avichr/heBERT_sentiment_analysis | 5,483 | 7 | transformers | 870 | ## HeBERT: Pre-trained BERT for Polarity Analysis and Emotion Recognition
HeBERT is a Hebrew pre-trained language model. It is based on Google's BERT architecture and it is BERT-Base config [(Devlin et al. 2018)](https://arxiv.org/abs/1810.04805). <br>
HeBert was trained on three datasets:
1. A Hebrew version of OSCA... |
microsoft/xtremedistil-l12-h384-uncased | dd970883b88410d02b66c408c8461eed0168e8a4 | 2021-08-05T17:49:31.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"en",
"arxiv:2106.04563",
"transformers",
"text-classification",
"license:mit"
] | text-classification | false | microsoft | null | microsoft/xtremedistil-l12-h384-uncased | 5,462 | 5 | transformers | 871 | ---
language: en
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
tags:
- text-classification
license: mit
---
# XtremeDistilTransformers for Distilling Massive Neural Networks
XtremeDistilTransformers is a distilled task-agnostic transformer model that leverages task transfer for learning a small uni... |
Langboat/mengzi-bert-base-fin | b7b290d3b4dd5ec87f47d3cf5d55c9d00bd69e59 | 2021-10-18T05:53:38.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"arxiv:2110.06696",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Langboat | null | Langboat/mengzi-bert-base-fin | 5,448 | 1 | transformers | 872 | ---
language:
- zh
license: apache-2.0
---
# Mengzi-BERT base fin model (Chinese)
Continue trained mengzi-bert-base with 20G financial news and research reports. Masked language modeling(MLM), part-of-speech(POS) tagging and sentence order prediction(SOP) are used as training task.
[Mengzi: Towards Lightweight yet ... |
aubmindlab/bert-base-arabertv02-twitter | 14bddd56ee5b02d1d92436ca14934687452a96ea | 2021-10-16T22:10:29.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"ar",
"dataset:wikipedia",
"dataset:OSIAN",
"dataset:1.5B Arabic Corpus",
"dataset:OSCAR Arabic Unshuffled",
"dataset:Twitter",
"arxiv:2003.00104",
"transformers",
"autotrain_compatible"
] | fill-mask | false | aubmindlab | null | aubmindlab/bert-base-arabertv02-twitter | 5,417 | null | transformers | 873 | ---
language: ar
datasets:
- wikipedia
- OSIAN
- 1.5B Arabic Corpus
- OSCAR Arabic Unshuffled
- Twitter
widget:
- text: " عاصمة لبنان هي [MASK] ."
---
<img src="https://raw.githubusercontent.com/aub-mind/arabert/master/arabert_logo.png" width="100" align="center"/>
# AraBERTv0.2-Twitter
AraBERTv0.2-Twitter-b... |
elastic/distilbert-base-cased-finetuned-conll03-english | 3043a315aae69b6e2f88056b23100e144791ac99 | 2022-06-24T09:30:31.000Z | [
"pytorch",
"distilbert",
"token-classification",
"en",
"dataset:conll2003",
"transformers",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | elastic | null | elastic/distilbert-base-cased-finetuned-conll03-english | 5,406 | 5 | transformers | 874 | ---
language: en
license: apache-2.0
datasets:
- conll2003
model-index:
- name: elastic/distilbert-base-cased-finetuned-conll03-english
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: conll2003
type: conll2003
config: conll2003
split: val... |
google/pegasus-pubmed | 27396b90fefc6b2f8365728fb1e23963d7feca2d | 2020-10-22T16:33:32.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"arxiv:1912.08777",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | google | null | google/pegasus-pubmed | 5,399 | 3 | transformers | 875 | ---
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: [@... |
symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli | e6331eecd7f50dd13c8ebcdc57a9f0a22f2ff56e | 2021-09-30T11:27:56.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"ru",
"th",
"tr",
"ur",
"vn",
"zh",
"dataset:SNLI",
"dataset:MNLI",
"dataset:ANLI",
"dataset:XNLI",
"sentence-transformers",
"zero-shot-classification",
"sentence-similarity",
"tra... | sentence-similarity | false | symanto | null | symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli | 5,392 | 5 | sentence-transformers | 876 | ---
language:
- ar
- bg
- de
- el
- en
- es
- fr
- ru
- th
- tr
- ur
- vn
- zh
datasets:
- SNLI
- MNLI
- ANLI
- XNLI
pipeline_tag: sentence-similarity
tags:
- zero-shot-classification
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
A Siamese network mode... |
dkleczek/bert-base-polish-cased-v1 | fed744e81ebd16cf099b5c64c40688bc3e6ace67 | 2021-05-19T15:54:20.000Z | [
"pytorch",
"jax",
"bert",
"pretraining",
"pl",
"transformers"
] | null | false | dkleczek | null | dkleczek/bert-base-polish-cased-v1 | 5,383 | null | transformers | 877 | ---
language: pl
thumbnail: https://raw.githubusercontent.com/kldarek/polbert/master/img/polbert.png
---
# Polbert - Polish BERT
Polish version of BERT language model is here! It is now available in two variants: cased and uncased, both can be downloaded and used via HuggingFace transformers library. I recommend using... |
microsoft/xtremedistil-l6-h384-uncased | 359df7d52613d4edc15647e6d65e0d87200eb747 | 2021-08-05T17:48:58.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"en",
"arxiv:2106.04563",
"transformers",
"text-classification",
"license:mit"
] | text-classification | false | microsoft | null | microsoft/xtremedistil-l6-h384-uncased | 5,374 | 16 | transformers | 878 | ---
language: en
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
tags:
- text-classification
license: mit
---
# XtremeDistilTransformers for Distilling Massive Neural Networks
XtremeDistilTransformers is a distilled task-agnostic transformer model that leverages task transfer for learning a small uni... |
Prime2911/DialoGPT-medium-handsomejack | c9d3196d32519f073bec0ce80aeb01abe78d8075 | 2022-03-11T07:54:11.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Prime2911 | null | Prime2911/DialoGPT-medium-handsomejack | 5,355 | null | transformers | 879 | ---
tags:
- conversational
---
# Handsome Jack DialoGPT Model |
microsoft/trocr-base-handwritten | bad90c41e8b5a5cd03f658fbd568b44b2ee047c5 | 2022-07-01T07:35:45.000Z | [
"pytorch",
"vision-encoder-decoder",
"arxiv:2109.10282",
"transformers",
"trocr",
"image-to-text"
] | image-to-text | false | microsoft | null | microsoft/trocr-base-handwritten | 5,344 | 8 | transformers | 880 | ---
tags:
- trocr
- image-to-text
---
# TrOCR (base-sized model, fine-tuned on IAM)
TrOCR model fine-tuned on the [IAM dataset](https://fki.tic.heia-fr.ch/databases/iam-handwriting-database). It was introduced in the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv... |
sentence-transformers/stsb-mpnet-base-v2 | 9f9d3d9da582d245066b519ab1e99c3f54a0594e | 2021-08-05T08:31:17.000Z | [
"pytorch",
"mpnet",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/stsb-mpnet-base-v2 | 5,332 | 2 | sentence-transformers | 881 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/stsb-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vec... |
zlucia/custom-legalbert | fd49a135d7b327a315e3ffea31c2be1b40685315 | 2021-07-02T05:56:40.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"en",
"arxiv:2104.08671",
"arxiv:1808.06226",
"transformers",
"legal",
"fill-mask"
] | fill-mask | false | zlucia | null | zlucia/custom-legalbert | 5,263 | 3 | transformers | 882 | ---
language: en
pipeline_tag: fill-mask
tags:
- legal
---
### Custom Legal-BERT
Model and tokenizer files for Custom Legal-BERT model from [When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset](https://arxiv.org/abs/2104.08671).
### Training Data
The pretraining corpus was ... |
patrickvonplaten/longformer-random-tiny | 8f15d46e686753d8c1ffb6e876fa90740a1c32c3 | 2020-08-05T09:22:23.000Z | [
"pytorch",
"tf",
"longformer",
"feature-extraction",
"transformers"
] | feature-extraction | false | patrickvonplaten | null | patrickvonplaten/longformer-random-tiny | 5,232 | null | transformers | 883 | Entry not found |
banden/DialoGPT-medium-RickBot | 010c54cb71eeb60b5a15b270842d132bde6254aa | 2021-09-21T14:58:30.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | banden | null | banden/DialoGPT-medium-RickBot | 5,231 | null | transformers | 884 | ---
tags:
- conversational
---
# Rick Sanchez DialoGPT Model |
princeton-nlp/unsup-simcse-roberta-large | d3f863b476c59b0673264042f159cea15842e265 | 2021-06-16T12:15:47.000Z | [
"pytorch",
"jax",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | princeton-nlp | null | princeton-nlp/unsup-simcse-roberta-large | 5,230 | null | transformers | 885 | Entry not found |
xlm-roberta-large-finetuned-conll03-german | 737aa82161f5a202e95012eebfe78ef597d980ec | 2022-07-22T08:06:55.000Z | [
"pytorch",
"rust",
"xlm-roberta",
"token-classification",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
... | token-classification | false | null | null | xlm-roberta-large-finetuned-conll03-german | 5,178 | null | transformers | 886 | ---
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
... |
sberbank-ai/sbert_large_nlu_ru | 28d04bde633f23feb22916430a01cdfcadfd35e9 | 2021-09-21T19:42:35.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"transformers",
"PyTorch",
"Transformers"
] | feature-extraction | false | sberbank-ai | null | sberbank-ai/sbert_large_nlu_ru | 5,159 | 5 | transformers | 887 | ---
language:
- ru
tags:
- PyTorch
- Transformers
---
# BERT large model (uncased) for Sentence Embeddings in Russian language.
The model is described [in this article](https://habr.com/ru/company/sberdevices/blog/527576/)
For better quality, use mean token embeddings.
## Usage (HuggingFace Models Repository)
You ... |
tunib/electra-ko-base | edfb795c9f667b3c5cb7085ca9112997823ce4e8 | 2021-09-28T07:48:06.000Z | [
"pytorch",
"electra",
"pretraining",
"arxiv:2003.10555",
"transformers"
] | null | false | tunib | null | tunib/electra-ko-base | 5,153 | 5 | transformers | 888 | # TUNiB-Electra
We release several new versions of the [ELECTRA](https://arxiv.org/abs/2003.10555) model, which we name TUNiB-Electra. There are two motivations. First, all the existing pre-trained Korean encoder models are monolingual, that is, they have knowledge about Korean only. Our bilingual models are based... |
vasudevgupta/bigbird-roberta-natural-questions | e073d287d7d8e6798f5081934b6de80a4f44a9ed | 2021-05-12T03:20:58.000Z | [
"pytorch",
"big_bird",
"question-answering",
"en",
"dataset:natural_questions",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | vasudevgupta | null | vasudevgupta/bigbird-roberta-natural-questions | 5,143 | 3 | transformers | 889 | ---
language: en
license: apache-2.0
datasets: natural_questions
widget:
- text: "Who added BigBird to HuggingFace Transformers?"
context: "BigBird Pegasus just landed! Thanks to Vasudev Gupta, BigBird Pegasus from Google AI is merged into HuggingFace Transformers. Check it out today!!!"
---
This checkpoint is obtai... |
Helsinki-NLP/opus-mt-ca-en | 22113f5e0e8e89677d6e0142e55c85402eecb455 | 2021-09-09T21:28:18.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ca",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ca-en | 5,133 | null | transformers | 890 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ca-en
* source languages: ca
* target languages: en
* OPUS readme: [ca-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ca-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
sberbank-ai/ruBert-base | 43be4261797042e172adf7476c558734f3cbb2a0 | 2022-05-08T14:17:32.000Z | [
"pytorch",
"bert",
"fill-mask",
"ru",
"transformers",
"PyTorch",
"Transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | sberbank-ai | null | sberbank-ai/ruBert-base | 5,112 | 5 | transformers | 891 | ---
language:
- ru
tags:
- PyTorch
- Transformers
- bert
- exbert
pipeline_tag: fill-mask
thumbnail: "https://github.com/sberbank-ai/model-zoo"
license: apache-2.0
---
# ruBert-large
Model was trained by [SberDevices](https://sberdevices.ru/) team.
* Task: `mask filling`
* Type: `encoder`
* Tokenizer: `bpe`
* Dict s... |
Helsinki-NLP/opus-mt-gmq-en | 74efbe7477ba9acf0bcc143fcad9f5280db2fab4 | 2021-01-18T08:52:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"da",
"nb",
"sv",
"is",
"nn",
"fo",
"gmq",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-gmq-en | 5,046 | null | transformers | 892 | ---
language:
- da
- nb
- sv
- is
- nn
- fo
- gmq
- en
tags:
- translation
license: apache-2.0
---
### gmq-eng
* source group: North Germanic languages
* target group: English
* OPUS readme: [gmq-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmq-eng/README.md)
* model: transformer
... |
facebook/s2t-small-mustc-en-fr-st | 90bd87c9a36fc51f1acb419760563551671e3b4e | 2022-02-07T14:44:08.000Z | [
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"en",
"fr",
"dataset:mustc",
"arxiv:2010.05171",
"arxiv:1904.08779",
"transformers",
"audio",
"speech-translation",
"license:mit"
] | automatic-speech-recognition | false | facebook | null | facebook/s2t-small-mustc-en-fr-st | 5,026 | 1 | transformers | 893 | ---
language:
- en
- fr
datasets:
- mustc
tags:
- audio
- speech-translation
- automatic-speech-recognition
license: mit
pipeline_tag: automatic-speech-recognition
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
sr... |
theta/MBTI-ckiplab-bert | 9e9a2f40a3dc8ecb7049937fbf6be5e596e25d6b | 2022-05-14T13:23:32.000Z | [
"pytorch",
"bert",
"text-classification",
"zh",
"transformers",
"MBTI",
"zh-tw",
"generated_from_trainer",
"model-index"
] | text-classification | false | theta | null | theta/MBTI-ckiplab-bert | 5,008 | null | transformers | 894 | ---
language:
- zh
tags:
- MBTI
- zh
- zh-tw
- generated_from_trainer
model-index:
- name: MBTI-ckiplab-bert
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. -->
# MB... |
sivasankalpp/dpr-multidoc2dial-structure-question-encoder | b18e46980a1551430338531a09213330d5fd5e96 | 2021-11-10T21:32:20.000Z | [
"pytorch",
"dpr",
"feature-extraction",
"transformers"
] | feature-extraction | false | sivasankalpp | null | sivasankalpp/dpr-multidoc2dial-structure-question-encoder | 5,001 | null | transformers | 895 | Entry not found |
seyonec/SMILES_tokenized_PubChem_shard00_160k | f0854db6cbaad4655ce3bb0c073b9ba0199f4a7d | 2021-05-20T21:08:23.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | seyonec | null | seyonec/SMILES_tokenized_PubChem_shard00_160k | 4,987 | null | transformers | 896 | Entry not found |
savasy/bert-base-turkish-ner-cased | d2853558b8a3b19639dce6da2d8a5b6d8f0102a0 | 2021-05-20T04:53:47.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"tr",
"transformers",
"autotrain_compatible"
] | token-classification | false | savasy | null | savasy/bert-base-turkish-ner-cased | 4,977 | 3 | transformers | 897 | ---
language: tr
---
# For Turkish language, here is an easy-to-use NER application.
** Türkçe için kolay bir python NER (Bert + Transfer Learning) (İsim Varlık Tanıma) modeli...
Thanks to @stefan-it, I applied the followings for training
cd tr-data
for file in train.txt dev.txt test.txt labels.txt
do
wget... |
SpanBERT/spanbert-base-cased | b436fe68816aa04256692ce7e27711bf6be15513 | 2021-05-19T11:30:27.000Z | [
"pytorch",
"jax",
"bert",
"transformers"
] | null | false | SpanBERT | null | SpanBERT/spanbert-base-cased | 4,951 | 2 | transformers | 898 | Entry not found |
yiyanghkust/finbert-esg | 26eff66d1942e399ca3ed598894cf0a52915985b | 2022-06-10T23:19:11.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"transformers",
"financial-text-analysis",
"esg",
"environmental-social-corporate-governance"
] | text-classification | false | yiyanghkust | null | yiyanghkust/finbert-esg | 4,932 | 5 | transformers | 899 | ---
language: "en"
tags:
- financial-text-analysis
- esg
- environmental-social-corporate-governance
widget:
- text: "Rhonda has been volunteering for several years for a variety of charitable community programs. "
---
ESG analysis can help investors determine a business' long-term sustainability and identify associat... |
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