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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Evelyn18/legalectra-small-spanish-becasv3-5 | 4a14fa0c3939dd56e182ffb7e6d52cfca86f3b58 | 2022-07-12T04:45:36.000Z | [
"pytorch",
"tensorboard",
"electra",
"question-answering",
"dataset:becasv2",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | Evelyn18 | null | Evelyn18/legalectra-small-spanish-becasv3-5 | 235 | null | transformers | 3,400 | ---
tags:
- generated_from_trainer
datasets:
- becasv2
model-index:
- name: legalectra-small-spanish-becasv3-5
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. -->
# ... |
google/ncsnpp-celebahq-256 | 17d28fd936ebceba39284f4d5b28946317325269 | 2022-07-21T15:00:03.000Z | [
"diffusers",
"arxiv:2011.13456",
"pytorch",
"unconditional-image-generation",
"license:apache-2.0"
] | unconditional-image-generation | false | google | null | google/ncsnpp-celebahq-256 | 235 | null | diffusers | 3,401 | ---
license: apache-2.0
tags:
- pytorch
- diffusers
- unconditional-image-generation
---
# Score-Based Generative Modeling through Stochastic Differential Equations (SDE)
**Paper**: [Score-Based Generative Modeling through Stochastic Differential Equations](https://arxiv.org/abs/2011.13456)
**Authors**: Yang Song, J... |
Helsinki-NLP/opus-mt-de-pl | 67458bb97566391315397d8e0aa5f14f774bd238 | 2021-09-09T21:32:59.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"pl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-pl | 234 | null | transformers | 3,402 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-de-pl
* source languages: de
* target languages: pl
* OPUS readme: [de-pl](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-pl/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
allenai/unifiedqa-v2-t5-large-1251000 | 5b84e7f94d0a24806d08dbb04ee872a351f83404 | 2022-02-22T00:36:48.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-v2-t5-large-1251000 | 234 | null | transformers | 3,403 | # Further details: https://github.com/allenai/unifiedqa
|
ionite/DialoGPT-medium-mohnjilesAI | bf581ec9b06e5fc6ded6e63aed6b2530be601732 | 2021-11-20T23:21:32.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ionite | null | ionite/DialoGPT-medium-mohnjilesAI | 234 | null | transformers | 3,404 | ---
tags:
- conversational
---
# mohnjilesAI DialoGPT Model |
jonatasgrosman/wav2vec2-large-xlsr-53-persian | ce183fdf22d071e80806023335ca7db222c3d86b | 2022-07-27T23:34:50.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"fa",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-large-xlsr-53-persian | 234 | 3 | transformers | 3,405 | ---
language: fa
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Persian by Jonatas Grosman
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM | 461cc35437ed5a10a43a5556c6b71a212db652f2 | 2022-06-27T15:28:20.000Z | [
"pytorch",
"tf",
"bart",
"text2text-generation",
"en",
"dataset:cnndaily/newyorkdaily/xsum/samsum/dialogsum",
"transformers",
"seq2seq",
"summarization",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | knkarthick | null | knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM | 234 | 1 | transformers | 3,406 | ---
language: en
tags:
- bart
- seq2seq
- summarization
license: apache-2.0
datasets:
- cnndaily/newyorkdaily/xsum/samsum/dialogsum
metrics:
- rouge
widget:
- text: |-
Hi, I'm David and I'm supposed to be an industrial designer. Um, I just got the project announcement about what the project is. Designing a remote c... |
razent/SciFive-base-Pubmed | 7ecd3e2966a97aa898461113a2dbb8da1acac625 | 2022-03-20T17:47:16.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"dataset:pubmed",
"arxiv:2106.03598",
"transformers",
"token-classification",
"text-classification",
"question-answering",
"text-generation",
"autotrain_compatible"
] | text-classification | false | razent | null | razent/SciFive-base-Pubmed | 234 | 1 | transformers | 3,407 | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
---
# SciFive Pubmed Base
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs/2106.03598)
Authors... |
textattack/xlnet-base-cased-rotten-tomatoes | d82af55dad548dfb89119b4664309e7cfa9e2053 | 2020-07-06T16:36:38.000Z | [
"pytorch",
"xlnet",
"text-generation",
"transformers"
] | text-generation | false | textattack | null | textattack/xlnet-base-cased-rotten-tomatoes | 234 | null | transformers | 3,408 | ## TextAttack Model Card
This `xlnet-base-cased` model was fine-tuned for sequence classification using TextAttack
and the rotten_tomatoes dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 16, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this... |
csebuetnlp/mT5_m2o_hindi_crossSum | 4246a0fc5df90077090cdb30f088ace8cecc3aaa | 2022-04-22T15:03:33.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"am",
"ar",
"az",
"bn",
"my",
"zh",
"en",
"fr",
"gu",
"ha",
"hi",
"ig",
"id",
"ja",
"rn",
"ko",
"ky",
"mr",
"ne",
"om",
"ps",
"fa",
"pcm",
"pt",
"pa",
"ru",
"gd",
"sr",
"si",
"so",
"es",
"sw",
"ta",
"te... | summarization | false | csebuetnlp | null | csebuetnlp/mT5_m2o_hindi_crossSum | 234 | null | transformers | 3,409 | ---
tags:
- summarization
- mT5
language:
- am
- ar
- az
- bn
- my
- zh
- en
- fr
- gu
- ha
- hi
- ig
- id
- ja
- rn
- ko
- ky
- mr
- ne
- om
- ps
- fa
- pcm
- pt
- pa
- ru
- gd
- sr
- si
- so
- es
- sw
- ta
- te
- th
- ti
- tr
- uk
- ur
- uz
- vi
- cy
- yo
licenses:
- cc-by-nc-sa-4.0
widget:
- text: "Videos that say a... |
t8oo/DialoGPT-small-zenigata | 43446068845204bf072d65420cf79021798ef7f6 | 2022-05-23T08:02:15.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | t8oo | null | t8oo/DialoGPT-small-zenigata | 234 | null | transformers | 3,410 | ---
tags:
- conversational
---
# Zenigata DialoGPT Model |
ck46/t5-base-hotpot-qa-qg | f74aba4b96c41f84ecadb68ed23824045b4647be | 2022-01-11T09:52:49.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ck46 | null | ck46/t5-base-hotpot-qa-qg | 233 | null | transformers | 3,411 | Entry not found |
flax-community/gpt-neo-125M-code-clippy-dedup-2048 | dcaced278779587969abf2780b49734cef1dcd1e | 2021-07-18T17:30:41.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | flax-community | null | flax-community/gpt-neo-125M-code-clippy-dedup-2048 | 233 | 4 | transformers | 3,412 | Entry not found |
healx/gpt-2-pubmed-medium | 6495202861edc7ea631c08d0892917d91255290c | 2020-12-11T21:43:41.000Z | [
"pytorch",
"arxiv:2004.13845",
"transformers"
] | null | false | healx | null | healx/gpt-2-pubmed-medium | 233 | null | transformers | 3,413 | GPT-2 (355M model) finetuned on 0.5m PubMed abstracts. Used in the [writemeanabstract.com](writemeanabstract.com) and the following preprint:
[Papanikolaou, Yannis, and Andrea Pierleoni. "DARE: Data Augmented Relation Extraction with GPT-2." arXiv preprint arXiv:2004.13845 (2020).](https://arxiv.org/abs/2004.13845)
|
moussaKam/frugalscore_medium_bert-base_mover-score | e4d050062a4188e213ca57bae5e22e2d689a5470 | 2022-05-11T11:07:21.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2110.08559",
"transformers"
] | text-classification | false | moussaKam | null | moussaKam/frugalscore_medium_bert-base_mover-score | 233 | null | transformers | 3,414 | # FrugalScore
FrugalScore is an approach to learn a fixed, low cost version of any expensive NLG metric, while retaining most of its original performance
Paper: https://arxiv.org/abs/2110.08559?context=cs
Project github: https://github.com/moussaKam/FrugalScore
The pretrained checkpoints presented in the paper :
| ... |
mrm8488/distilroberta-finetuned-age_news-classification | 2c7aff917a107ea45621627217f3e63adb8ce6b7 | 2021-05-20T18:23:35.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"en",
"dataset:ag_news",
"transformers",
"news",
"classification"
] | text-classification | false | mrm8488 | null | mrm8488/distilroberta-finetuned-age_news-classification | 233 | 1 | transformers | 3,415 | ---
language: en
tags:
- news
- classification
datasets:
- ag_news
widget:
- text: "Venezuela Prepares for Chavez Recall Vote Supporters and rivals warn of possible fraud; government says Chavez's defeat could produce turmoil in world oil market."
---
# distilroberta-base fine-tuned on age_news dataset for news classi... |
patrickvonplaten/unispeech-large-1500h-cv-timit | 084bb18d5c0ae406b34156887764c43d19db33aa | 2021-10-27T10:50:16.000Z | [
"pytorch",
"tensorboard",
"unispeech",
"automatic-speech-recognition",
"dataset:timit_asr",
"transformers",
"timit_asr",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/unispeech-large-1500h-cv-timit | 233 | null | transformers | 3,416 | ---
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: unispeech-large-1500h-cv-timit
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and compl... |
smilesandtea/DialoGPT-medium-Rick | 5438cc37710aaa5fe9f6523bb4f63a59eea18c99 | 2021-12-06T19:27:03.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | smilesandtea | null | smilesandtea/DialoGPT-medium-Rick | 233 | null | transformers | 3,417 | ---
tags:
- conversational
---
# Rick DialoGPT Model |
tau/splinter-large-qass | 317a7d0f7432d4bbae0e4187257f20e425ff154b | 2021-09-03T08:47:23.000Z | [
"pytorch",
"splinter",
"question-answering",
"en",
"arxiv:2108.05857",
"transformers",
"SplinterModel",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | tau | null | tau/splinter-large-qass | 233 | 0 | transformers | 3,418 | ---
language: en
tags:
- splinter
- SplinterModel
license: apache-2.0
---
# Splinter large model, (with pretrained QASS-layer weights)
Splinter-large is the pretrained model discussed in the paper [Few-Shot Question Answering by Pretraining Span Selection](https://aclanthology.org/2021.acl-long.239/) (at ACL 2021)... |
Intel/bert-base-uncased-mrpc | 014e870f64e3c1376952bf518a8cdb9e95df20f7 | 2022-04-06T08:13:30.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Intel | null | Intel/bert-base-uncased-mrpc | 233 | null | transformers | 3,419 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metric... |
alibaba-pai/pai-bert-tiny-zh | 4acdb9757ebe593f0e65f829339a8818a90094e1 | 2022-06-10T02:34:43.000Z | [
"pytorch",
"bert",
"zh",
"arxiv:2205.00258",
"transformers",
"license:apache-2.0",
"fill-mask"
] | fill-mask | false | alibaba-pai | null | alibaba-pai/pai-bert-tiny-zh | 233 | 1 | transformers | 3,420 | ---
language: zh
pipeline_tag: fill-mask
widget:
- text: "中国的首都是北[MASK]。"
- text: "牛奶是[MASK]色的。"
tags:
- bert
license: apache-2.0
---
## Alibaba PAI BERT Tiny Chinese
This project provides Chinese pre-trained language models and various types of NLP tools. The models are pre-trained on the large-scale corpora hosted b... |
joaoalvarenga/bloom-8bit | 8d1adb1b9642666dfe80d87440e690b3f974ca20 | 2022-07-14T00:12:48.000Z | [
"pytorch",
"bloom",
"text-generation",
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
"rw",
"sn",
"st",
"sw",
"ta",
"te",... | text-generation | false | joaoalvarenga | null | joaoalvarenga/bloom-8bit | 233 | 41 | transformers | 3,421 | ---
inference: false
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zu
pipeline_tag: text-generat... |
helpmefindaname/mini-sequence-tagger-conll03 | d8fbd8898a209e1264fb2abef3af852ad3a56a4b | 2022-07-19T00:53:03.000Z | [
"pytorch",
"en",
"dataset:conll2003",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | helpmefindaname | null | helpmefindaname/mini-sequence-tagger-conll03 | 233 | null | flair | 3,422 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language: en
datasets:
- conll2003
widget:
- text: "George Washington went to Washington"
---
This is a very small model I use for testing my [ner eval dashboard](https://github.com/helpmefindaname/ner-eval-dashboard)
F1-Score: **48,73** (CoNLL-03)
P... |
bespin-global/klue-sentence-roberta-base | 6cc0ac3cdf46e4ebeaae46e385b6dda316548a6d | 2022-02-07T07:14:05.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"dataset:klue",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:cc-by-nc-4.0"
] | sentence-similarity | false | bespin-global | null | bespin-global/klue-sentence-roberta-base | 232 | null | sentence-transformers | 3,423 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- klue
license: cc-by-nc-4.0
---
# bespin-global/klue-sentence-roberta-base
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 di... |
hfl/chinese-electra-small-generator | dd271ca037299a9b0d2d389c9c65c3e28c2d8f49 | 2021-03-03T01:38:55.000Z | [
"pytorch",
"tf",
"electra",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0",
"fill-mask"
] | fill-mask | false | hfl | null | hfl/chinese-electra-small-generator | 232 | null | transformers | 3,424 | ---
language:
- zh
license: "apache-2.0"
pipeline_tag: "fill-mask"
---
**Please use `ElectraForPreTraining` for `discriminator` and `ElectraForMaskedLM` for `generator` if you are re-training these models.**
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has ... |
sibyl/BART-commongen | 5993c052a6432e12c319069fad44bfd45b1d02a0 | 2021-08-09T22:24:43.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"dataset:gem",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | false | sibyl | null | sibyl/BART-commongen | 232 | null | transformers | 3,425 | ---
tags:
- generated_from_trainer
datasets:
- gem
model_index:
- name: BART-commongen
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gem
type: gem
args: common_gen
---
<!-- This model card has been generated automatically a... |
TheBakerCat/2chan_ruGPT3_small | ae88dc55e1e0f80876e0478bb5ac90699324066c | 2021-05-21T11:26:24.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | TheBakerCat | null | TheBakerCat/2chan_ruGPT3_small | 231 | null | transformers | 3,426 | ruGPT3-small model, trained on some 2chan posts
|
codistai/codeBERT-small-v2 | 01695bc17a6157b5e24cb003c8d0b0ce88c87894 | 2021-05-20T15:35:42.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | codistai | null | codistai/codeBERT-small-v2 | 231 | null | transformers | 3,427 | Entry not found |
fgaim/tiroberta-base | 4e81446260c169a8cf3ff7f1a9e4f5c04e5f8e9c | 2021-10-08T00:07:07.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"ti",
"transformers",
"autotrain_compatible"
] | fill-mask | false | fgaim | null | fgaim/tiroberta-base | 231 | 1 | transformers | 3,428 | ---
language: ti
widget:
- text: "ዓቕሚ መንእሰይ ኤርትራ <mask> ተራእዩ"
---
# RoBERTa Pretrained for Tigrinya Language
We pretrain a RoBERTa base model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs.
Contained in this repo is the original pretrained Flax model that was trained on a TPU v3.8 and it's corr... |
google/bert_uncased_L-4_H-128_A-2 | c29bee83fc7f003ac8c5e6e135529da4ecddb7c3 | 2021-05-19T17:30:08.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-4_H-128_A-2 | 231 | null | transformers | 3,429 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... |
liam168/trans-opus-mt-zh-en | 85f60aa282af51009c10912996c377ec4f68385c | 2021-07-16T03:34:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"zh",
"transformers",
"translation",
"autotrain_compatible"
] | translation | false | liam168 | null | liam168/trans-opus-mt-zh-en | 231 | null | transformers | 3,430 | ---
language:
- en
- zh
tags:
- translation
widget:
- text: "我喜欢学习数据科学和机器学习。"
---
# liam168/trans-opus-mt-zh-en
## Model description
* source group: English
* target group: Chinese
* model: transformer
* source language(s): eng
## How to use
```python
>>> from transformers import AutoModelWithLMHead,AutoToke... |
lonewanderer27/DialoGPT-small-Joshua | 7de3318f53e928b825cda8e67171f1f7507d1b09 | 2021-08-23T15:15:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | lonewanderer27 | null | lonewanderer27/DialoGPT-small-Joshua | 231 | null | transformers | 3,431 | ---
tags:
- conversational
---
# Joshua DialoGPT Model |
pucpr/gpt2-bio-pt | 28356b33732dbe98a5eb1f81bec7a01b0062d035 | 2021-07-22T21:30:05.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"pt",
"dataset:biomedical literature from Scielo and Pubmed",
"transformers"
] | text-generation | false | pucpr | null | pucpr/gpt2-bio-pt | 231 | 4 | transformers | 3,432 | ---
language: "pt"
widget:
- text: "O paciente recebeu "
- text: "A cardiologia provou que "
- text: "O paciente chegou no hospital "
- text: "Cientistas descobriram que "
- text: "O nível de atividade biológica "
- text: "O DNA e o RNA "
datasets:
- biomedical literature from Scielo and Pubmed
thumbnail: "https://ra... |
tprincessazula/Dialog-GPT-small-AANG | 6437f08ecf00ba83af90008ccc017e886c8eca82 | 2021-12-19T10:13:07.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | tprincessazula | null | tprincessazula/Dialog-GPT-small-AANG | 231 | 1 | transformers | 3,433 | ---
tags:
- conversational
---
# AAng Dialog-GPT Model |
Helsinki-NLP/opus-mt-de-it | cd2319a082a7be0dd471fe62701ae557a71833c2 | 2021-09-09T21:32:05.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"it",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-it | 230 | null | transformers | 3,434 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-de-it
* source languages: de
* target languages: it
* OPUS readme: [de-it](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-it/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
MoritzLaurer/DeBERTa-v3-base-mnli-fever-docnli-ling-2c | 29f90c4b7bbbaec52e99d1ee1f6f0aa3301d1d61 | 2022-07-28T16:23:48.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"arxiv:2104.07179",
"arxiv:2106.09449",
"arxiv:2006.03654",
"arxiv:2111.09543",
"transformers",
"zero-shot-classification",
"license:mit"
] | text-classification | false | MoritzLaurer | null | MoritzLaurer/DeBERTa-v3-base-mnli-fever-docnli-ling-2c | 230 | 3 | transformers | 3,435 | ---
language:
- en
license: mit
tags:
- text-classification
- zero-shot-classification
metrics:
- accuracy
widget:
- text: "I first thought that I liked the movie, but upon second thought it was actually disappointing. [SEP] The movie was good."
---
# DeBERTa-v3-base-mnli-fever-docnli-ling-2c
## Model description
Thi... |
jb2k/bert-base-multilingual-cased-language-detection | aa4473be53d456ad2ae216a2048f002dae00c920 | 2021-11-24T01:36:01.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | jb2k | null | jb2k/bert-base-multilingual-cased-language-detection | 230 | 2 | transformers | 3,436 | # bert-base-multilingual-cased-language-detection
A model for language detection with support for 45 languages
## Model description
This model was created by fine-tuning
[bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the [common language](https://huggingface.co/datasets/common_l... |
miguelvictor/multilingual-gpt2-large | d3f3a185b1c31018552090c6881e7b10581d5953 | 2021-05-23T09:24:27.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | miguelvictor | null | miguelvictor/multilingual-gpt2-large | 230 | 1 | transformers | 3,437 | Entry not found |
sonoisa/byt5-small-japanese | 851ce1d7642798766fa1a053178f9080b1fe275d | 2021-09-23T16:29:53.000Z | [
"pytorch",
"mt5",
"ja",
"dataset:wikipedia",
"dataset:oscar",
"dataset:cc100",
"transformers",
"byt5",
"t5",
"text2text-generation",
"seq2seq",
"license:cc-by-sa-4.0"
] | text2text-generation | false | sonoisa | null | sonoisa/byt5-small-japanese | 230 | 3 | transformers | 3,438 | ---
language: ja
tags:
- byt5
- t5
- text2text-generation
- seq2seq
license: cc-by-sa-4.0
datasets:
- wikipedia
- oscar
- cc100
---
# 日本語ByT5事前学習済みモデル
This is a [ByT5 (a tokenizer-free extension of the Text-to-Text Transfer Transformer)](https://github.com/google-research/byt5/) model pretrained on Japanese corpus.
... |
toyfreak/DialoGPT-small-addy | 9effa898d8b2fed24c03a5f65c0ad6ce0320ec5e | 2022-01-11T00:48:27.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | toyfreak | null | toyfreak/DialoGPT-small-addy | 230 | null | transformers | 3,439 | ---
tags:
- conversational
---
# Addy DialoGPT Model |
wolfrage89/company_segment_ner | 1e9e906d37778502136c50531084a76d3376ffcf | 2022-01-27T16:56:23.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | wolfrage89 | null | wolfrage89/company_segment_ner | 230 | null | transformers | 3,440 | ## Roberta based NER
This model will take in a new article label 3 entities [ORGS, SEGNUM, NUM]. This model is train on reuters news articles
## Try out on huggingface Spaces
https://huggingface.co/spaces/wolfrage89/company_segments_ner
## colab sample notebook
https://colab.research.google.com/drive/165utMQzYVAX7-aQ... |
datarpit/distilbert-base-uncased-finetuned-natural-questions | 28400e5824c250ea3fac5f53da0fee11e03dfd4d | 2022-03-16T07:52:09.000Z | [
"pytorch",
"distilbert",
"question-answering",
"dataset:natural_questions",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | datarpit | null | datarpit/distilbert-base-uncased-finetuned-natural-questions | 230 | 1 | transformers | 3,441 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- natural_questions
model-index:
- name: distilbert-base-uncased-finetuned-natural-questions
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and... |
luohy/rgx-qa-v2 | d4e1af690cc4be3d52fa7d9f06002d918e23eb1e | 2022-06-29T13:05:16.000Z | [
"pytorch",
"electra",
"question-answering",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | question-answering | false | luohy | null | luohy/rgx-qa-v2 | 230 | null | transformers | 3,442 | ---
license: afl-3.0
---
|
MCFeli/new-booru-t5 | 7ab30857fc801ca428c69066d889c30eadfb0ba2 | 2022-07-10T13:53:20.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | MCFeli | null | MCFeli/new-booru-t5 | 230 | null | transformers | 3,443 | Entry not found |
Rajan/NepaliBERT | 996c3b86b779a63225b473221678447c9d9185d0 | 2021-06-07T14:36:58.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Rajan | null | Rajan/NepaliBERT | 229 | null | transformers | 3,444 |
# NepaliBERT(Phase 1)
NEPALIBERT is a state-of-the-art language model for Nepali based on the BERT model. The model is trained using a masked language modeling (MLM).
# Loading the model and tokenizer
1. clone the model repo
```
git lfs install
git clone https://huggingface.co/Rajan/NepaliBERT
```
2. Loading the ... |
allenai/dsp_roberta_base_dapt_cs_tapt_citation_intent_1688 | 326cb08451b42ab268e57ee0e62a78558b435a0e | 2021-05-20T13:08:32.000Z | [
"pytorch",
"jax",
"roberta",
"transformers"
] | null | false | allenai | null | allenai/dsp_roberta_base_dapt_cs_tapt_citation_intent_1688 | 229 | null | transformers | 3,445 | Entry not found |
dandelin/vilt-b32-finetuned-nlvr2 | d72f414aeb17ccbc50114a64346b3ce4bb6954b1 | 2022-01-23T09:43:30.000Z | [
"pytorch",
"vilt",
"arxiv:2102.03334",
"transformers",
"license:apache-2.0"
] | null | false | dandelin | null | dandelin/vilt-b32-finetuned-nlvr2 | 229 | 1 | transformers | 3,446 | ---
license: apache-2.0
---
# Vision-and-Language Transformer (ViLT), fine-tuned on NLVR2
Vision-and-Language Transformer (ViLT) model fine-tuned on [NLVR2](https://lil.nlp.cornell.edu/nlvr/). It was introduced in the paper [ViLT: Vision-and-Language Transformer
Without Convolution or Region Supervision](https://arxi... |
google/roberta2roberta_L-24_discofuse | 6e27093f8bae22e876a8a8a9f2857babaecb33f4 | 2020-12-11T21:43:12.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"en",
"dataset:discofuse",
"arxiv:1907.12461",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/roberta2roberta_L-24_discofuse | 229 | null | transformers | 3,447 | ---
language: en
license: apache-2.0
datasets:
- discofuse
---
# Roberta2Roberta_L-24_discofuse 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/bertseq2se... |
pere/norwegian-gpt2-social | 31b9c1fe79e7eab73d0f466cdf60952c3c1a49f0 | 2021-11-01T11:01:55.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"no",
"transformers",
"norwegian",
"GPT2",
"casual language modeling",
"license:cc-by-4.0"
] | text-generation | false | pere | null | pere/norwegian-gpt2-social | 229 | null | transformers | 3,448 | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- GPT2
- casual language modeling
---
# Norwegian GPT-2 - Social
## Description
Experimental Norwegian GPT-2-model trained on a 37GB mainly social corpus.
The following sub-corpora are used:
```bash
wikipedia_download_nb.jsonl
wikipedia_download_nn.jsonl
newspape... |
rovai/chatbotmedium3 | 2831d18c91f89213f4079ebeed92c30ac73fb68a | 2021-12-01T16:19:29.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | rovai | null | rovai/chatbotmedium3 | 229 | null | transformers | 3,449 | ---
tags:
- conversational
---
# chatbotmedium3 |
Salesforce/codegen-350M-nl | 170f13a3699e3bde3bdb61970dcb1c9c2954c5c1 | 2022-06-28T17:47:41.000Z | [
"pytorch",
"codegen",
"text-generation",
"arxiv:2203.13474",
"transformers",
"license:bsd-3-clause"
] | text-generation | false | Salesforce | null | Salesforce/codegen-350M-nl | 229 | null | transformers | 3,450 | ---
license: bsd-3-clause
---
# CodeGen (CodeGen-NL 350M)
## 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 Wa... |
AnnaWegmann/Style-Embedding | c098de52c64898eaf32d1eeb36fc19ed27695525 | 2022-05-20T07:46:47.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | AnnaWegmann | null | AnnaWegmann/Style-Embedding | 229 | null | sentence-transformers | 3,451 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# Style Embedding
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clus... |
speechbrain/sepformer-wham16k-enhancement | 30f979f4814a0a401e7558994cec647e537e505d | 2022-07-01T01:03:12.000Z | [
"en",
"dataset:WHAM!",
"arxiv:2010.13154",
"arxiv:2106.04624",
"speechbrain",
"audio-to-audio",
"Speech Enhancement",
"WHAM!",
"SepFormer",
"Transformer",
"pytorch",
"license:apache-2.0"
] | audio-to-audio | false | speechbrain | null | speechbrain/sepformer-wham16k-enhancement | 229 | 1 | speechbrain | 3,452 | ---
language: "en"
thumbnail:
tags:
- audio-to-audio
- Speech Enhancement
- WHAM!
- SepFormer
- Transformer
- pytorch
- speechbrain
license: "apache-2.0"
datasets:
- WHAM!
metrics:
- SI-SNR
- PESQ
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v... |
wbbbbb/wav2vec2-large-chinese-zh-cn | 369f73139f85a98570ff74e641dc93d421a3860e | 2022-07-18T10:12:44.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"pretraining",
"zh",
"dataset:common_voice",
"transformers",
"audio",
"automatic-speech-recognition",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | wbbbbb | null | wbbbbb/wav2vec2-large-chinese-zh-cn | 229 | 1 | transformers | 3,453 | ---
language: zh
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Chinese (zh-CN) by wbbbbb
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
jeanconstantin/distilcausal_bert_fr | 3967575923e6805ef04f14449a92ebe21c869ea1 | 2022-07-21T20:18:57.000Z | [
"pytorch",
"camembert",
"text-classification",
"transformers"
] | text-classification | false | jeanconstantin | null | jeanconstantin/distilcausal_bert_fr | 229 | null | transformers | 3,454 | Entry not found |
SEBIS/code_trans_t5_base_commit_generation_multitask_finetune | 5d4f07a9c2ab6564a5461cda17ac167423880e92 | 2021-06-23T05:00:29.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_base_commit_generation_multitask_finetune | 228 | null | transformers | 3,455 | ---
tags:
- summarization
widget:
- text: "new file mode 100644 index 000000000 . . 892fda21b Binary files / dev / null and b / src / plugins / gateway / lib / joscar . jar differ"
---
# CodeTrans model for git commit message generation
Pretrained model on git commit using the t5 base model architecture. It was firs... |
ftnvir/DialoGPT-medium-bullyMaguire | 9717913bb04393e7d7852965814e427b5eea6726 | 2022-01-25T14:09:02.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ftnvir | null | ftnvir/DialoGPT-medium-bullyMaguire | 228 | null | transformers | 3,456 | ---
tags:
- conversational
---
#Bully Maguire demo bot |
lserinol/bert-turkish-question-answering | 791f71680be796c2785d23eb29baeb805d1ec16c | 2021-05-19T22:06:55.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"tr",
"transformers",
"autotrain_compatible"
] | question-answering | false | lserinol | null | lserinol/bert-turkish-question-answering | 228 | 1 | transformers | 3,457 | ---
language: tr
---
# bert-turkish-question-answering
## Usage
```python
from transformers import pipeline
nlp = pipeline('question-answering', model='lserinol/bert-turkish-question-answering', tokenizer='lserinol/bert-turkish-question-answering')
nlp({
'question': "Ankara'da kaç ilçe vardır?",
'context': r... |
thesamuelpena/Dialog-medium-masterchief | 48be93ebdf3679158a219727e03af58c022bbf95 | 2021-11-14T01:18:14.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | thesamuelpena | null | thesamuelpena/Dialog-medium-masterchief | 228 | null | transformers | 3,458 | ---
tags:
- conversational
---
# Master Chief DialoGPT Model |
Shakerlicious/DialoGPT-small-descentbot | 1593849331f7159103fbf3e2e1b562d460005dcb | 2022-05-03T04:40:13.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Shakerlicious | null | Shakerlicious/DialoGPT-small-descentbot | 228 | null | transformers | 3,459 | ---
tags:
- conversational
---
# Sergio bot DialoGPT Model |
kakife3586/Ekastestest | 42429f8ee7d163bf0bbcc9b925f59fcf2f0bbff0 | 2022-07-09T03:21:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | kakife3586 | null | kakife3586/Ekastestest | 228 | null | transformers | 3,460 | Entry not found |
Backedman/DialoGPT-small-Anika | c9bdba4e72530104497b5686bdd0bd11bd8c00c3 | 2021-11-18T15:16:27.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Backedman | null | Backedman/DialoGPT-small-Anika | 227 | null | transformers | 3,461 | ---
tags:
- conversational
---
#Anika Bot |
KoichiYasuoka/roberta-large-english-upos | c0e2ec7cc128a0a18e974307380f3b3ddf4e7494 | 2022-02-16T03:16:33.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"dataset:universal_dependencies",
"transformers",
"english",
"pos",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/roberta-large-english-upos | 227 | 0 | transformers | 3,462 | ---
language:
- "en"
tags:
- "english"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
---
# roberta-large-english-upos
## Model Description
This is a RoBERTa model pre-trained with [UD_English](https://universa... |
armheb/DNA_bert_3 | ed28178e378645f8582810a667e3a152960bb847 | 2021-10-10T22:26:24.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | armheb | null | armheb/DNA_bert_3 | 227 | null | transformers | 3,463 | Entry not found |
cahya/gpt2-large-indonesian-522M | 9d01a8304f15c1f0d2216b64eb6f8ec5e9f0f7c3 | 2021-05-21T14:39:08.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | cahya | null | cahya/gpt2-large-indonesian-522M | 227 | null | transformers | 3,464 | Entry not found |
cross-encoder/nli-deberta-v3-xsmall | d922ed00ccc227f499505cc6207fcc1e58938cb3 | 2021-12-27T22:27:20.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"dataset:multi_nli",
"dataset:snli",
"transformers",
"microsoft/deberta-v3-xsmall",
"license:apache-2.0",
"zero-shot-classification"
] | zero-shot-classification | false | cross-encoder | null | cross-encoder/nli-deberta-v3-xsmall | 227 | 2 | transformers | 3,465 | ---
language: en
pipeline_tag: zero-shot-classification
tags:
- microsoft/deberta-v3-xsmall
datasets:
- multi_nli
- snli
metrics:
- accuracy
license: apache-2.0
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.ne... |
ethzanalytics/distilgpt2-tiny-conversational | 374785cb7942780b7f3fcd8cc28dd972630aa189 | 2022-07-21T06:33:55.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"chatbot",
"dialogue",
"distilgpt2",
"ai-msgbot",
"license:apache-2.0"
] | text-generation | false | ethzanalytics | null | ethzanalytics/distilgpt2-tiny-conversational | 227 | null | transformers | 3,466 | ---
license: apache-2.0
tags:
- text-generation
- chatbot
- dialogue
- distilgpt2
- gpt2
- ai-msgbot
widget:
- text: "I know you're tired, but can we go for another walk this evening?\nperson beta:\n\n"
example_title: "walk"
- text: "Have you done anything exciting lately?\nperson beta:\n\n"
example_title: "activ... |
nvidia/segformer-b0-finetuned-cityscapes-768-768 | c837d6d06664132b0c9a98e25c4459ee3807643d | 2022-07-20T09:54:23.000Z | [
"pytorch",
"tf",
"segformer",
"dataset:cityscapes",
"arxiv:2105.15203",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | nvidia | null | nvidia/segformer-b0-finetuned-cityscapes-768-768 | 227 | null | transformers | 3,467 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- cityscapes
widget:
- src: https://www.researchgate.net/profile/Anurag-Arnab/publication/315881952/figure/fig5/AS:667673876779033@1536197265755/Sample-results-on-the-Cityscapes-dataset-The-above-images-show-how-our-method-can-handle.jpg
example_ti... |
solfer/DialoGPT-small-ryuji | 16aab55c1797a1040dbabc07c5943952cf16dcc0 | 2021-08-30T04:36:57.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | solfer | null | solfer/DialoGPT-small-ryuji | 227 | null | transformers | 3,468 | ---
tags:
- conversational
---
# Ryuji DialoGPT Model |
ssspider/DialoGPT-medium-harrypotter | df8cb343ad8edf8b1cc6065c020604d9e3d20c7c | 2021-12-25T17:09:42.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ssspider | null | ssspider/DialoGPT-medium-harrypotter | 226 | null | transformers | 3,469 | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model |
thu-coai/LongLM-large | 461383ecc756769255023947ddc22001e5bd3656 | 2022-01-10T15:44:33.000Z | [
"pytorch",
"t5",
"text2text-generation",
"zh",
"arxiv:2108.12960",
"transformers",
"lm-head",
"autotrain_compatible"
] | text2text-generation | false | thu-coai | null | thu-coai/LongLM-large | 226 | 4 | transformers | 3,470 | ---
language:
- zh
thumbnail: http://coai.cs.tsinghua.edu.cn/coai/img/logo.png?v=13923
tags:
- pytorch
- lm-head
- zh
widget:
- text: "小咕噜对靳司寒完全是个自来熟，小家伙爬进他怀里小手搂着他的脖子，奶声奶气的要求：“靳蜀黎,你给咕噜讲故事好不好？”讲故事？童话故事吗？“我不会。”小家伙明显不信。嘟着小嘴大眼汪汪的盯着他，“哼。”小家伙轻轻哼了一声,靳司寒默了半晌，<extra_id_1>"
- text: "美女亲自打招呼，这可是破天荒第一次，之前不管他献多少次殷勤，美女<extra_id_1>甩他... |
SkolkovoInstitute/Mutual_Implication_Score | 3d2a208cf3bbca5cc26a150d95d20c48ab1081eb | 2022-07-11T12:36:45.000Z | [
"pytorch",
"roberta",
"en",
"transformers",
"paraphrase detection",
"paraphrase",
"paraphrasing"
] | null | false | SkolkovoInstitute | null | SkolkovoInstitute/Mutual_Implication_Score | 226 | null | transformers | 3,471 | ---
language:
- en
tags:
- paraphrase detection
- paraphrase
- paraphrasing
licenses:
- cc-by-nc-sa
---
## Model overview
Mutual Implication Score is a symmetric measure of text semantic similarity
based on a RoBERTA model pretrained for natural language inference
and fine-tuned on a paraphrase detection dataset.
... |
surrey-nlp/roberta-base-finetuned-abbr | a905959f197275955f52eef71c452c6355bd0f91 | 2022-04-30T12:17:39.000Z | [
"pytorch",
"tf",
"roberta",
"token-classification",
"dataset:surrey-nlp/PLOD-filtered",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | surrey-nlp | null | surrey-nlp/roberta-base-finetuned-abbr | 226 | 1 | transformers | 3,472 | ---
model_creators:
- Leonardo Zilio, Hadeel Saadany, Prashant Sharma, Diptesh Kanojia, Constantin Orasan
license: mit
tags:
- generated_from_trainer
datasets:
- surrey-nlp/PLOD-filtered
metrics:
- precision
- recall
- f1
- accuracy
widget:
- text: "Light dissolved inorganic carbon (DIC) resulting from the oxidation ... |
markofhope/DialoGPT-medium-HarringtonBot | 161b8bdd6768190bde819abe69208bd26180aa02 | 2022-06-14T07:04:17.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | markofhope | null | markofhope/DialoGPT-medium-HarringtonBot | 226 | null | transformers | 3,473 | ---
tags:
- conversational
---
#HarringtonBot dialogue model |
JdThe65th/GPT2-Glitchfur-Zenith-JD | 9b3e2d9767959526803f6403670eb11930ff6756 | 2022-06-23T00:21:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | JdThe65th | null | JdThe65th/GPT2-Glitchfur-Zenith-JD | 226 | null | transformers | 3,474 | ---
language: en
thumbnail: http://www.huggingtweets.com/glitchfur-jdthe65th-zenitho_o/1655941045991/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; marg... |
Helsinki-NLP/opus-mt-am-sv | 4ee236b77a2559c6c94f3fbef5228dc28c7929fe | 2021-09-09T21:26:12.000Z | [
"pytorch",
"marian",
"text2text-generation",
"am",
"sv",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-am-sv | 225 | null | transformers | 3,475 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-am-sv
* source languages: am
* target languages: sv
* OPUS readme: [am-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/am-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-en-af | c6a79302395db2b59af8b15f4016081a66095ace | 2021-09-09T21:34:05.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"af",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-af | 225 | null | transformers | 3,476 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-af
* source languages: en
* target languages: af
* OPUS readme: [en-af](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-af/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
MingZhong/DialogLED-large-5120 | b6c71369f2fee0cbc99178f7ab681dfbf9d8d09f | 2022-01-05T07:36:41.000Z | [
"pytorch",
"led",
"text2text-generation",
"arxiv:2109.02492",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | MingZhong | null | MingZhong/DialogLED-large-5120 | 225 | 2 | transformers | 3,477 | [DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization](https://arxiv.org/abs/2109.02492).
## Introduction
DialogLED is a pre-trained model for long dialogue understanding and summarization. It builds on the Longformer-Encoder-Decoder (LED) architecture and uses window-based denoising as the pr... |
clue/roberta_chinese_3L312_clue_tiny | 5c87eb26d6ca701f3badaacbeebb37b878bbd9aa | 2021-05-20T15:22:48.000Z | [
"pytorch",
"jax",
"roberta",
"zh",
"arxiv:2003.01355",
"transformers"
] | null | false | clue | null | clue/roberta_chinese_3L312_clue_tiny | 225 | 1 | transformers | 3,478 | ---
language: zh
---
# Introduction
This model was trained on TPU and the details are as follows:
## Model
##
| Model_name | params | size | Training_corpus | Vocab |
| :------------------------------------------ | :----- | :------- | :----------------- | :--... |
google/bert_uncased_L-12_H-512_A-8 | 58975ac76f4442555b5cd68848df3e0838a832bb | 2021-05-19T17:26:55.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-12_H-512_A-8 | 225 | null | transformers | 3,479 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... |
rovai/AI | 0e8e5055c2254b438256d250e3351bcd3fe8faad | 2021-12-01T23:52:04.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | rovai | null | rovai/AI | 225 | null | transformers | 3,480 | ---
tags:
- conversational
- gpt2
---
#MIHO |
sberbank-ai/bert-base-NER-reptile-5-datasets | feb2dcd088bf24fde96b3f53f720ac148fb678ef | 2022-02-04T10:51:07.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"dataset:conll2003",
"dataset:wnut_17",
"dataset:jnlpba",
"dataset:conll2012",
"dataset:BTC",
"dataset:dfki-nlp/few-nerd",
"arxiv:2010.02405",
"transformers",
"PyTorch",
"model-index",
"autotrain_compatible"
] | token-classification | false | sberbank-ai | null | sberbank-ai/bert-base-NER-reptile-5-datasets | 225 | 3 | transformers | 3,481 | ---
language:
- en
inference: false
pipeline_tag: false
datasets:
- conll2003
- wnut_17
- jnlpba
- conll2012
- BTC
- dfki-nlp/few-nerd
tags:
- PyTorch
model-index:
- name: "bert-base-NER-reptile-5-datasets"
results:
- task:
name: few-shot-ner
type: named-entity-recognition
dataset:
name: few-... |
youscan/ukr-roberta-base | f8689ddd740b7a3277f5205cd1d5dc5481699bb5 | 2021-05-20T23:23:40.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"uk",
"transformers",
"autotrain_compatible"
] | fill-mask | false | youscan | null | youscan/ukr-roberta-base | 225 | 5 | transformers | 3,482 | ---
language:
- uk
---
# ukr-roberta-base
## Pre-training corpora
Below is the list of corpora used along with the output of wc command (counting lines, words and characters). These corpora were concatenated and tokenized with HuggingFace Roberta Tokenizer.
| Tables | Lines | Words | Characters |
... |
GanjinZero/coder_eng | eb359315c38881c03d445e08614101ac9b214f1e | 2022-04-25T02:19:42.000Z | [
"pytorch",
"bert",
"feature-extraction",
"en",
"transformers",
"biomedical",
"license:apache-2.0"
] | feature-extraction | false | GanjinZero | null | GanjinZero/coder_eng | 224 | 1 | transformers | 3,483 | ---
language:
- en
license: apache-2.0
tags:
- bert
- biomedical
---
CODER: Knowledge infused cross-lingual medical term embedding for term normalization.
English Version.
```
@article{YUAN2022103983,
title = {CODER: Knowledge-infused cross-lingual medical term embedding for term normalization},
journal = {Journa... |
lgris/bp400-xlsr | 22bd0ba76c39569ce00a2133870d641d367fbee9 | 2022-04-01T20:31:02.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:common_voice",
"dataset:mls",
"dataset:cetuc",
"dataset:lapsbm",
"dataset:voxforge",
"dataset:tedx",
"dataset:sid",
"arxiv:2107.11414",
"arxiv:2012.03411",
"transformers",
"audio",
"speech",
"portuguese-speech-corp... | automatic-speech-recognition | false | lgris | null | lgris/bp400-xlsr | 224 | 2 | transformers | 3,484 | ---
language: pt
datasets:
- common_voice
- mls
- cetuc
- lapsbm
- voxforge
- tedx
- sid
metrics:
- wer
tags:
- audio
- speech
- wav2vec2
- pt
- portuguese-speech-corpus
- automatic-speech-recognition
- speech
- PyTorch
- hf-asr-leaderboard
model-index:
- name: bp400-xlsr
results:
- task:
name: Automatic Spe... |
pritamdeka/S-Bluebert-snli-multinli-stsb | a823c84f078a8323c58d0e8bd0fd3d311c508738 | 2022-01-28T16:23:12.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | pritamdeka | null | pritamdeka/S-Bluebert-snli-multinli-stsb | 224 | 1 | sentence-transformers | 3,485 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluster... |
swtx/ernie-3.0-base-chinese | 22c12393ee7a5cf78bf22c1a1c8704baff06b77d | 2022-07-26T14:58:41.000Z | [
"pytorch",
"arxiv:2106.02241",
"arxiv:2112.12731",
"transformers",
"license:apache-2.0"
] | null | false | swtx | null | swtx/ernie-3.0-base-chinese | 224 | 1 | transformers | 3,486 | ---
license: apache-2.0
---
# ERNIE 3.0 轻量级模型
**目录**
* [模型介绍](#模型介绍)
* [在线蒸馏技术](#在线蒸馏技术)
* [模型效果](#模型效果)
* [微调](#微调)
* [模型压缩](#模型压缩)
* [环境依赖](#环境依赖)
* [模型压缩 API 使用](#模型压缩API使用)
* [压缩效果](#压缩效果)
* [精度测试](#精度测试)
* [性能测试](#性能测试)
* [CPU 性能](#CPU... |
lisaterumi/postagger-portuguese | 3f35db993e5ceffbc56a85f11fd608ab30c0f44e | 2022-07-25T21:40:35.000Z | [
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:MacMorpho",
"transformers",
"autotrain_compatible"
] | token-classification | false | lisaterumi | null | lisaterumi/postagger-portuguese | 224 | 1 | transformers | 3,487 | ---
language: "pt"
widget:
- text: "Tinha uma pedra no meio do caminho."
- text: "Vamos tomar um café quentinho?"
- text: "Como você se chama?"
datasets:
- MacMorpho
---
# POS-Tagger Portuguese
We fine-tuned the [BERTimbau](https://github.com/neuralmind-ai/portuguese-bert/) model with the [MacMorpho](http://nilc.icm... |
ionite/DialoGPT-medium-NakaAI | d3906a0dfa6f54491862af0249e5fb15d317aa3b | 2022-07-20T07:12:36.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ionite | null | ionite/DialoGPT-medium-NakaAI | 224 | null | transformers | 3,488 | ---
tags:
- conversational
---
# NakaAI DialoGPT Model |
Helsinki-NLP/opus-mt-en-trk | 54a2a1aa579bd6b91d0f97dac094c0ae81c75902 | 2021-01-18T08:18:08.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"tt",
"cv",
"tk",
"tr",
"ba",
"trk",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-trk | 223 | 0 | transformers | 3,489 | ---
language:
- en
- tt
- cv
- tk
- tr
- ba
- trk
tags:
- translation
license: apache-2.0
---
### eng-trk
* source group: English
* target group: Turkic languages
* OPUS readme: [eng-trk](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-trk/README.md)
* model: transformer
* source lang... |
SEBIS/legal_t5_small_summ_it | 1811eb0c9d38453c2cc244ab9b53dd2d4d32c637 | 2021-06-23T11:23:40.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"Italian",
"dataset:jrc-acquis",
"transformers",
"summarization Italian model",
"autotrain_compatible"
] | text2text-generation | false | SEBIS | null | SEBIS/legal_t5_small_summ_it | 222 | null | transformers | 3,490 |
---
language: Italian
tags:
- summarization Italian model
datasets:
- jrc-acquis
widget:
- text: "LA COMMISSIONE DELLE COMUNITÀ EUROPEE, visto il trattato che istituisce la Comunità europea, visto il regolamento (CEE) n. 2082/92 del Consiglio, del 14 luglio 1992, relativo alle attestazioni di specificità dei prodot... |
ethanyt/guwen-sent | 2bd35fb055cf935093e63a0534ab042668451f21 | 2021-06-18T04:51:54.000Z | [
"pytorch",
"roberta",
"text-classification",
"zh",
"transformers",
"chinese",
"classical chinese",
"literary chinese",
"ancient chinese",
"bert",
"sentiment classificatio",
"license:apache-2.0"
] | text-classification | false | ethanyt | null | ethanyt/guwen-sent | 222 | 2 | transformers | 3,491 | ---
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"
- "sentiment classificatio"
license: "apache-2.0"
pipeline_tag: "text-classificatio... |
cynthiachan/finetuned-10pct-cti | 5b950cbf07e4799a806b5a85b66f4c249b55d6a1 | 2022-07-15T08:23:34.000Z | [
"pytorch",
"bert",
"token-classification",
"dataset:cynthiachan/FeedRef_10pct",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | cynthiachan | null | cynthiachan/finetuned-10pct-cti | 222 | null | transformers | 3,492 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cynthiachan/FeedRef_10pct
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: training_3
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cynthiachan/FeedRef_10pct
type:... |
bigscience/distill-bloom-1b3 | 44d410716eb93a1cc796e5ac45fc8d7e57a81b1d | 2022-07-18T09:01:28.000Z | [
"pytorch",
"bloom",
"feature-extraction",
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
"rw",
"sn",
"st",
"sw",
... | text-generation | false | bigscience | null | bigscience/distill-bloom-1b3 | 222 | null | transformers | 3,493 | ---
license: bigscience-bloom-rail-1.0
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zhs
- zht
- zu
pipeline_tag: text-gener... |
dbmdz/electra-base-ukrainian-cased-generator | 2f854462bb1b3da0a2b033a2dd8280906f62c164 | 2020-11-10T21:15:17.000Z | [
"pytorch",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/electra-base-ukrainian-cased-generator | 221 | null | transformers | 3,494 | Entry not found |
ionite/DialoGPT-medium-orangeAI | 70f8eea3121cb0768be68531ec999377de8bd55c | 2021-11-07T18:01:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ionite | null | ionite/DialoGPT-medium-orangeAI | 221 | 1 | transformers | 3,495 | ---
tags:
- conversational
---
# orangeAI DialoGPT Model |
marefa-nlp/marefa-ner | 97150023f089d776bf025950d1e4506625c71c34 | 2021-12-04T05:21:57.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"ar",
"dataset:Marefa-NER",
"transformers",
"autotrain_compatible"
] | token-classification | false | marefa-nlp | null | marefa-nlp/marefa-ner | 221 | 2 | transformers | 3,496 |
---
language: ar
datasets:
- Marefa-NER
widget:
- text: "في استاد القاهرة، بدأ حفل افتتاح بطولة كأس الأمم الأفريقية بحضور رئيس الجمهورية و رئيس الاتحاد الدولي لكرة القدم"
---
# Tebyan تبيـان
## Marefa Arabic Named Entity Recognition Model
## نموذج المعرفة لتصنيف أجزاء النص
<p align="center">
<img src="... |
prithivida/active_to_passive_styletransfer | d3deb88bab2ae342e5233d160eb0d454d7eb2f57 | 2021-06-23T13:43:58.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | prithivida | null | prithivida/active_to_passive_styletransfer | 221 | 1 | transformers | 3,497 | ## This model belongs to the Styleformer project
[Please refer to github page](https://github.com/PrithivirajDamodaran/Styleformer)
|
rovai/chatbotmedium1 | b3d784b91ae6ab681c6dcd55f65ce0bc67f23793 | 2021-12-01T14:06:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | rovai | null | rovai/chatbotmedium1 | 221 | null | transformers | 3,498 | ---
tags:
- conversational
---
# chatbot |
ELiRF/NASES | 9e805fe577912dbfea0519d0dbf576d8bd6efb94 | 2022-04-21T14:12:01.000Z | [
"pytorch",
"bart",
"text2text-generation",
"es",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | ELiRF | null | ELiRF/NASES | 220 | 1 | transformers | 3,499 | ---
language: es
tags:
- summarization
widget:
- text: "La Agencia Valenciana de la Innovación (AVI) financia el desarrollo de un software que integra diferentes modelos y tecnologías para la monitorización y análisis multilingüe de las redes sociales. A través de técnicas de 'deep learning' y procesamiento del lengu... |
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