modelId stringlengths 4 112 | sha stringlengths 40 40 | lastModified stringlengths 24 24 | tags list | pipeline_tag stringclasses 29
values | private bool 1
class | author stringlengths 2 38 ⌀ | config null | id stringlengths 4 112 | downloads float64 0 36.8M ⌀ | likes float64 0 712 ⌀ | library_name stringclasses 17
values | __index_level_0__ int64 0 38.5k | readme stringlengths 0 186k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
unicamp-dl/mMiniLM-L6-v2-mmarco-v2 | 8ed6820748716827e99e8f39505eaa121169c1a1 | 2022-01-05T22:45:15.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"pt",
"dataset:msmarco",
"arxiv:2108.13897",
"transformers",
"msmarco",
"miniLM",
"tensorflow",
"pt-br",
"license:mit"
] | text-classification | false | unicamp-dl | null | unicamp-dl/mMiniLM-L6-v2-mmarco-v2 | 122 | null | transformers | 4,300 | ---
language: pt
license: mit
tags:
- msmarco
- miniLM
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- msmarco
widget:
- text: "Texto de exemplo em português"
inference: false
---
# mMiniLM-L6-v2 Reranker finetuned on mMARCO
## Introduction
mMiniLM-L6-v2-mmarco-v2 is a multilingual miniLM-based model finetuned on a mul... |
pszemraj/t5-v1_1-base-ft-jflAUG | bf9384f2c638632ef0e943ec57ddb7b13f7f6740 | 2022-07-10T00:41:01.000Z | [
"pytorch",
"t5",
"text2text-generation",
"dataset:jfleg",
"transformers",
"grammar",
"spelling",
"punctuation",
"error-correction",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | pszemraj | null | pszemraj/t5-v1_1-base-ft-jflAUG | 122 | 1 | transformers | 4,301 | ---
license: cc-by-nc-sa-4.0
tags:
- grammar
- spelling
- punctuation
- error-correction
datasets:
- jfleg
widget:
- text: "i can has cheezburger"
example_title: "cheezburger"
- text: "There car broke down so their hitching a ride to they're class."
example_title: "compound-1"
- text: "so em if we have an now so wi... |
algoprog/mimics-multilabel-roberta-base-787 | 7faaa092ba7eea4b0389b572322a365560405c92 | 2022-05-07T17:49:07.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | algoprog | null | algoprog/mimics-multilabel-roberta-base-787 | 122 | null | transformers | 4,302 | Entry not found |
IljaSamoilov/EstBERT-estonian-subtitles-token-classification | ceabdc298a4ff421f22d990d715f2409e9757391 | 2022-05-11T08:13:06.000Z | [
"pytorch",
"bert",
"token-classification",
"et",
"transformers",
"autotrain_compatible"
] | token-classification | false | IljaSamoilov | null | IljaSamoilov/EstBERT-estonian-subtitles-token-classification | 122 | null | transformers | 4,303 | ---
language:
- et
widget:
- text: "Et, et, et miks mitte olla siis tasakaalus, ma noh, hüpoteetiliselt viskan selle palli üles,"
- text: "te olete ka noh, noh, päris korralikult ka Rahvusringhäälingu teatud mõttes sellisesse keerulisse olukorda pannud,"
---
Importing the model and tokenizer:
```
tokenizer = Auto... |
launch/POLITICS | 41b3da20755e0eaf6f00a9dfc5136f4920721856 | 2022-07-26T00:06:33.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | launch | null | launch/POLITICS | 122 | 3 | transformers | 4,304 | ## POLITICS
POLITICS, a pretrained model on English news articles of politics, is produced via continued training on RoBERTa, based on a **P**retraining **O**bjective **L**everaging **I**nter-article **T**riplet-loss using **I**deological **C**ontent and **S**tory.
Details of our proposed training objectives (i.e., I... |
fourthbrain-demo/model_trained_by_me2 | 0fdf6cf2c394fd10fb3740b1a4fc937da49643d3 | 2022-06-20T20:47:13.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | fourthbrain-demo | null | fourthbrain-demo/model_trained_by_me2 | 122 | null | transformers | 4,305 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: model_trained_by_me2
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 comme... |
HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi | 76f7785ba3d6e867239401bc6359678a92505e4c | 2021-05-18T20:58:01.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | HooshvareLab | null | HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi | 121 | null | transformers | 4,306 | ---
language: fa
license: apache-2.0
---
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](... |
algolet/mt5-base-chinese-qg | 90f1d65a0fb2129463110b272d275f88fe57d22c | 2022-03-03T02:18:05.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"zh",
"transformers",
"question generation",
"autotrain_compatible"
] | text2text-generation | false | algolet | null | algolet/mt5-base-chinese-qg | 121 | 4 | transformers | 4,307 | <h3 align="center">
<p>MT5 Base Model for Chinese Question Generation</p>
</h3>
<h3 align="center">
<p>基于mt5的中文问题生成任务</p>
</h3>
#### 可以通过安装question-generation包开始用
```
pip install question-generation
```
使用方法请参考github项目：https://github.com/algolet/question_generation
#### 在线使用
可以直接在线使用我们的模型：https://www.algolet.... |
avichr/hebEMO_anticipation | 27b2152fa2a8875fe4f5cc438e21a413bbc36fa4 | 2022-04-15T09:35:11.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | avichr | null | avichr/hebEMO_anticipation | 121 | null | transformers | 4,308 | # HebEMO - Emotion Recognition Model for Modern Hebrew
<img align="right" src="https://github.com/avichaychriqui/HeBERT/blob/main/data/heBERT_logo.png?raw=true" width="250">
HebEMO is a tool that detects polarity and extracts emotions from modern Hebrew User-Generated Content (UGC), which was trained on a unique Covid... |
facebook/s2t-small-mustc-en-de-st | ebde73eef775bb11dfa33ee2e5285e0fcfc6f126 | 2022-02-07T15:07:57.000Z | [
"pytorch",
"tf",
"speech_to_text",
"automatic-speech-recognition",
"en",
"de",
"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-de-st | 121 | null | transformers | 4,309 | ---
language:
- en
- de
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... |
facebook/wav2vec2-xls-r-2b-21-to-en | e045eaf53c335796df62992c1aee949a1c20d32c | 2022-05-27T03:01:36.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"multilingual",
"fr",
"de",
"es",
"ca",
"it",
"ru",
"zh",
"pt",
"fa",
"et",
"mn",
"nl",
"tr",
"ar",
"sv",
"lv",
"sl",
"ta",
"ja",
"id",
"cy",
"en",
"dataset:common_voice",
"dataset:multilingual... | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-xls-r-2b-21-to-en | 121 | 1 | transformers | 4,310 | ---
language:
- multilingual
- fr
- de
- es
- ca
- it
- ru
- zh
- pt
- fa
- et
- mn
- nl
- tr
- ar
- sv
- lv
- sl
- ta
- ja
- id
- cy
- en
datasets:
- common_voice
- multilingual_librispeech
- covost2
tags:
- speech
- xls_r
- automatic-speech-recognition
- xls_r_translation
pipeline_tag: automatic-speech-recognition
li... |
huggingtweets/commanderwuff | f9c9c97d7f1ba3f1f8932541096b5d6302dd307d | 2021-05-21T23:15:31.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/commanderwuff | 121 | null | transformers | 4,311 | ---
language: en
thumbnail: https://www.huggingtweets.com/commanderwuff/1614170164099/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/13639308885... |
ktangri/gpt-neo-demo | dbb3415f20cb5679e122ebe4bc6126b82f44cfa2 | 2021-07-21T15:20:09.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"en",
"dataset:the Pile",
"transformers",
"text generation",
"the Pile",
"causal-lm",
"license:apache-2.0"
] | text-generation | false | ktangri | null | ktangri/gpt-neo-demo | 121 | 1 | transformers | 4,312 | ---
language:
- en
tags:
- text generation
- pytorch
- the Pile
- causal-lm
license: apache-2.0
datasets:
- the Pile
---
# GPT-Neo 2.7B (By EleutherAI)
## Model Description
GPT-Neo 2.7B is a transformer model designed using EleutherAI's replication of the GPT-3 architecture. GPT-Neo refers to the class of models, while... |
macedonizer/hr-gpt2 | 4913a36f6dfb05ef6ff5eb89638cadc3843d19f0 | 2021-09-22T08:58:40.000Z | [
"pytorch",
"gpt2",
"text-generation",
"hr",
"dataset:wiki-hr",
"transformers",
"license:apache-2.0"
] | text-generation | false | macedonizer | null | macedonizer/hr-gpt2 | 121 | 1 | transformers | 4,313 | ---
language:
- hr
thumbnail: https://huggingface.co/macedonizer/hr-gpt2/lets-talk-about-nlp-hr.jpg
license: apache-2.0
datasets:
- wiki-hr
---
# hr-gpt2
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
Pretrained model on English language using a causal language modeling ... |
tau/spider | d06abf763de54af0e2a908610cd1fa1917ca3bba | 2022-05-08T07:51:30.000Z | [
"pytorch",
"dpr",
"arxiv:2112.07708",
"transformers"
] | null | false | tau | null | tau/spider | 121 | 5 | transformers | 4,314 | # Spider
This is the unsupervised pretrained model discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, so the same model should be applied for both.
**Note**! We format the passages s... |
facebook/m2m100-12B-last-ckpt | d3b4890e87cd5ee681d200e66d2aa5faf3a00feb | 2022-05-26T22:26:23.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"ast",
"az",
"ba",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"ceb",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"ff",
"fi",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha"... | text2text-generation | false | facebook | null | facebook/m2m100-12B-last-ckpt | 121 | null | transformers | 4,315 | ---
language:
- multilingual
- af
- am
- ar
- ast
- az
- ba
- be
- bg
- bn
- br
- bs
- ca
- ceb
- cs
- cy
- da
- de
- el
- en
- es
- et
- fa
- ff
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- ht
- hu
- hy
- id
- ig
- ilo
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- lb
- lg
- ln
- lo
- lt
- lv
- mg
- mk
- ... |
VietAI/vit5-large | 8a6430bc250119f4e587b541fb9511fabcb1145d | 2022-07-25T14:15:38.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"vi",
"dataset:cc100",
"transformers",
"summarization",
"translation",
"question-answering",
"license:mit",
"autotrain_compatible"
] | question-answering | false | VietAI | null | VietAI/vit5-large | 121 | null | transformers | 4,316 | ---
language: vi
datasets:
- cc100
tags:
- summarization
- translation
- question-answering
license: mit
---
# ViT5-large
State-of-the-art pretrained Transformer-based encoder-decoder model for Vietnamese.
## How to use
For more details, do check out [our Github repo](https://github.com/vietai/ViT5).
```python
fro... |
benjamin/gpt2-large-wechsel-ukrainian | 43593df16479731a30227a4cfb62be8ca731eb53 | 2022-04-29T16:56:10.000Z | [
"pytorch",
"gpt2",
"text-generation",
"uk",
"arxiv:2112.06598",
"transformers",
"license:mit"
] | text-generation | false | benjamin | null | benjamin/gpt2-large-wechsel-ukrainian | 121 | 3 | transformers | 4,317 | ---
license: mit
language: uk
---
# gpt2-large-wechsel-ukrainian
[`gpt2-large`](https://huggingface.co/gpt2-large) transferred to Ukrainian using the method from the NAACL2022 paper [WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models](https://arxiv.org/ab... |
jonas/sdg_classifier_osdg | c86a6802a2e2956365669a3ab41091d2634da058 | 2022-05-24T15:46:51.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:jonas/osdg_sdg_data_processed",
"transformers",
"co2_eq_emissions"
] | text-classification | false | jonas | null | jonas/sdg_classifier_osdg | 121 | 2 | transformers | 4,318 | ---
language: en
widget:
- text: "Ending all forms of discrimination against women and girls is not only a basic human right, but it also crucial to accelerating sustainable development. It has been proven time and again, that empowering women and girls has a multiplier effect, and helps drive up economic growth and de... |
PrimeQA/tydiqa-primary-task-xlm-roberta-large | 6933c572b917c8987b756c4202d6af1e4851ee1a | 2022-07-05T16:47:31.000Z | [
"pytorch",
"xlm-roberta",
"multilingual",
"arxiv:2003.05002",
"arxiv:1911.02116",
"transformers",
"MRC",
"TyDiQA",
"xlm-roberta-large"
] | null | false | PrimeQA | null | PrimeQA/tydiqa-primary-task-xlm-roberta-large | 121 | null | transformers | 4,319 | ---
tags:
- MRC
- TyDiQA
- xlm-roberta-large
language:
- multilingual
---
# Model description
An XLM-RoBERTa reading comprehension model for [TyDiQA Primary Tasks](https://arxiv.org/abs/2003.05002).
The model is initialized with [xlm-roberta-large](https://huggingface.co/xlm-roberta-large/) and fine-tuned on the [T... |
nickmuchi/yolos-small-rego-plates-detection | 232139b5fd2fcaeb45ccd59de5c8eda1fe0788fe | 2022-07-10T13:09:55.000Z | [
"pytorch",
"yolos",
"object-detection",
"dataset:coco",
"dataset:license-plate-detection",
"arxiv:2106.00666",
"transformers",
"license-plate-detection",
"vehicle-detection",
"license:apache-2.0",
"model-index"
] | object-detection | false | nickmuchi | null | nickmuchi/yolos-small-rego-plates-detection | 121 | null | transformers | 4,320 | ---
license: apache-2.0
tags:
- object-detection
- license-plate-detection
- vehicle-detection
datasets:
- coco
- license-plate-detection
widget:
- src: https://drive.google.com/uc?id=1j9VZQ4NDS4gsubFf3m2qQoTMWLk552bQ
example_title: "Skoda 1"
- src: https://drive.google.com/uc?id=1p9wJIqRz3W50e2f_A0D8ftla8hoXz4T5
e... |
TurkuNLP/wikibert-base-vi-cased | 359e6c23f7737b19861f4db02fd4484e2ecb639c | 2020-05-24T20:02:25.000Z | [
"pytorch",
"transformers"
] | null | false | TurkuNLP | null | TurkuNLP/wikibert-base-vi-cased | 120 | null | transformers | 4,321 | Entry not found |
erst/xlm-roberta-base-finetuned-nace | 84d9e5e01eb7a718c4ade662b6659509b73c17c0 | 2021-05-21T04:36:28.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | erst | null | erst/xlm-roberta-base-finetuned-nace | 120 | 1 | transformers | 4,322 | # Classifying Text into NACE Codes
This model is [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) fine-tuned to classify descriptions of activities into [NACE Rev. 2](https://ec.europa.eu/eurostat/web/nace-rev2) codes.
## Data
The data used to fine-tune the model consist of 2.5 million descriptions of act... |
ethanyt/guwen-cls | 3249168f65e7a2d6e1ad8fb09bd1e77db714ff90 | 2021-06-17T09:37:37.000Z | [
"pytorch",
"roberta",
"text-classification",
"zh",
"transformers",
"chinese",
"classical chinese",
"literary chinese",
"ancient chinese",
"bert",
"text classificatio",
"license:apache-2.0"
] | text-classification | false | ethanyt | null | ethanyt/guwen-cls | 120 | 1 | transformers | 4,323 | ---
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"
- "text classificatio"
license: "apache-2.0"
pipeline_tag: "text-classification"
wi... |
facebook/convnext-xlarge-384-22k-1k | f9f3d83b87a2a395b2ffa940a5ce7a0442c390e5 | 2022-03-02T19:02:58.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-21k",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-xlarge-384-22k-1k | 120 | 2 | transformers | 4,324 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-21k
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teap... |
gagan3012/k2t-new | 986e0baaec1fe1b014df182d1a24718ef2eb9c29 | 2021-09-22T08:27:25.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:common_gen",
"transformers",
"keytotext",
"k2t",
"Keywords to Sentences",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | gagan3012 | null | gagan3012/k2t-new | 120 | null | transformers | 4,325 | ---
language: en
thumbnail: Keywords to Sentences
tags:
- keytotext
- k2t
- Keywords to Sentences
license: mit
datasets:
- common_gen
metrics:
- NLG
---
# keytotext
Idea is to build a model which ... |
google/tapas-small-finetuned-wtq | b76ab837755d1c4dc4dc70eb7bade9b9fa5641c6 | 2022-07-14T10:13:43.000Z | [
"pytorch",
"tf",
"tapas",
"table-question-answering",
"en",
"dataset:wikitablequestions",
"arxiv:2004.02349",
"arxiv:2010.00571",
"arxiv:1508.00305",
"transformers",
"license:apache-2.0"
] | table-question-answering | false | google | null | google/tapas-small-finetuned-wtq | 120 | null | transformers | 4,326 | ---
language: en
tags:
- tapas
- table-question-answering
license: apache-2.0
datasets:
- wikitablequestions
---
# TAPAS small model fine-tuned on WikiTable Questions (WTQ)
This model has 2 versions which can be used. The default version corresponds to the `tapas_wtq_wikisql_sqa_inter_masklm_small_reset` checkpoint o... |
jonatasgrosman/wav2vec2-large-xlsr-53-hungarian | 07c68507b5d7c39f6c956a8ecca0658704ba99c9 | 2022-07-27T23:35:50.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"hu",
"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-hungarian | 120 | 1 | transformers | 4,327 | ---
language: hu
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 Hungarian by Jonatas Grosman
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
kingabzpro/wav2vec2-large-xls-r-300m-Urdu | ab77a3c4d65e4fcb8fc453072e1db45a1c224db4 | 2022-03-23T18:29:40.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ur",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | kingabzpro | null | kingabzpro/wav2vec2-large-xls-r-300m-Urdu | 120 | 1 | transformers | 4,328 | ---
language:
- ur
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-Urdu
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition... |
macedonizer/sl-gpt2 | e2626dcd4ff050db045efb829d5a477a79c75898 | 2021-09-22T08:58:51.000Z | [
"pytorch",
"gpt2",
"text-generation",
"sl",
"dataset:wiki-sl",
"transformers",
"license:apache-2.0"
] | text-generation | false | macedonizer | null | macedonizer/sl-gpt2 | 120 | null | transformers | 4,329 | ---
language:
- sl
thumbnail: https://huggingface.co/macedonizer/mkgpt2/lets-talk-about-nlp.jpg
license: apache-2.0
datasets:
- wiki-sl
---
# sl-gpt2
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
Pretrained model on English language using a causal language modeling (CLM... |
mgrella/autonlp-bank-transaction-classification-5521155 | cb26734f92f251e77874ed46ff6d5db067180e3d | 2021-07-22T21:32:58.000Z | [
"pytorch",
"bert",
"text-classification",
"it",
"dataset:mgrella/autonlp-data-bank-transaction-classification",
"transformers",
"autonlp"
] | text-classification | false | mgrella | null | mgrella/autonlp-bank-transaction-classification-5521155 | 120 | 1 | transformers | 4,330 | ---
tags: autonlp
language: it
widget:
- text: "I love AutoNLP 🤗"
datasets:
- mgrella/autonlp-data-bank-transaction-classification
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 5521155
## Validation Metrics
- Loss: 1.3173143863677979
- Accuracy: 0.8220706757594545
- Macro... |
rifkat/robert_BPE_pubchem10M | 0abbfed74087f4d0e9702b451fc0552a8afd9bbf | 2021-07-24T19:42:19.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | rifkat | null | rifkat/robert_BPE_pubchem10M | 120 | null | transformers | 4,331 | Entry not found |
ICFNext/EYY-categorisation-1.0 | 4737cf4193d111ae4eafbf4f4fb24719f620ee68 | 2022-03-24T00:16:47.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | ICFNext | null | ICFNext/EYY-categorisation-1.0 | 120 | 2 | transformers | 4,332 | Entry not found |
anegi/t5smallmodel | bc1b68bdefedc3f897fbc4135ce4612a74dc6c57 | 2022-04-09T03:37:45.000Z | [
"pytorch",
"t5",
"text2text-generation",
"dataset:samsum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | anegi | null | anegi/t5smallmodel | 120 | 1 | transformers | 4,333 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: t5smallmodel
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. -->
# t5s... |
Helsinki-NLP/opus-mt-tc-big-el-en | 559cab1eb5383f61552207d4ddca1e96e41d327e | 2022-06-01T13:01:32.000Z | [
"pytorch",
"marian",
"text2text-generation",
"el",
"en",
"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-el-en | 120 | null | transformers | 4,334 | ---
language:
- el
- en
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-el-en
results:
- task:
name: Translation ell-eng
type: translation
args: ell-eng
dataset:
name: flores101-devtest
type: flores_101
args: ell eng devtest
metrics... |
Team-PIXEL/pixel-base-finetuned-sst2 | 5a15269d904ad983d3cc4f23dd31704d83e9ee59 | 2022-07-14T19:18:25.000Z | [
"pytorch",
"pixel",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | Team-PIXEL | null | Team-PIXEL/pixel-base-finetuned-sst2 | 120 | null | transformers | 4,335 | ---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
model-index:
- name: pixel-base-finetuned-sst2
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. -->
... |
SkolkovoInstitute/gpt2-base-gedi-detoxification | aef170a95b65a27211bf66658e499f963a4a781f | 2021-11-02T18:07:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | SkolkovoInstitute | null | SkolkovoInstitute/gpt2-base-gedi-detoxification | 119 | null | transformers | 4,336 | Entry not found |
allenai/unifiedqa-v2-t5-3b-1363200 | 290d6c9755263e8d3c39dfb75c0401f356713492 | 2022-02-22T05:22:32.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-v2-t5-3b-1363200 | 119 | 1 | transformers | 4,337 | # Further details: https://github.com/allenai/unifiedqa
|
allenai/wmt16-en-de-12-1 | 1739470889a0567220bcd17202a8a904b3e10a11 | 2020-12-11T21:33:17.000Z | [
"pytorch",
"fsmt",
"text2text-generation",
"en",
"de",
"dataset:wmt16",
"arxiv:2006.10369",
"transformers",
"translation",
"wmt16",
"allenai",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | allenai | null | allenai/wmt16-en-de-12-1 | 119 | null | transformers | 4,338 |
---
language:
- en
- de
thumbnail:
tags:
- translation
- wmt16
- allenai
license: apache-2.0
datasets:
- wmt16
metrics:
- bleu
---
# FSMT
## Model description
This is a ported version of fairseq-based [wmt16 transformer](https://github.com/jungokasai/deep-shallow/) for en-de.
For more details, please, see [Deep En... |
anirudh21/albert-base-v2-finetuned-qnli | e5b34bf25b9ba48e02034b3045fa895744e537be | 2022-01-24T19:56:19.000Z | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | anirudh21 | null | anirudh21/albert-base-v2-finetuned-qnli | 119 | 1 | transformers | 4,339 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: albert-base-v2-finetuned-qnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: qnli
metrics:
- name: Acc... |
bayartsogt/mongolian-roberta-large | f74a5dac3521789bed8128930412186834856cba | 2021-08-23T03:59:52.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | bayartsogt | null | bayartsogt/mongolian-roberta-large | 119 | null | transformers | 4,340 | Entry not found |
doc2query/all-t5-base-v1 | 28d82c068119c6cf21945bfa8d91ce1dcbdfdf8d | 2021-10-19T12:54:25.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:sentence-transformers/reddit-title-body",
"dataset:sentence-transformers/embedding-training-data",
"arxiv:1904.08375",
"arxiv:2104.08663",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | doc2query | null | doc2query/all-t5-base-v1 | 119 | 1 | transformers | 4,341 | ---
language: en
datasets:
- sentence-transformers/reddit-title-body
- sentence-transformers/embedding-training-data
widget:
- text: "Python is an interpreted, high-level and general-purpose programming language. Python's design philosophy emphasizes code readability with its notable use of significant whitespace... |
laxya007/gpt2_BE_ISI_NE_BI_INR | 95a376be2883dee847c0675493ec107224cf07c0 | 2021-05-23T06:42:28.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | laxya007 | null | laxya007/gpt2_BE_ISI_NE_BI_INR | 119 | null | transformers | 4,342 | Entry not found |
w11wo/indonesian-roberta-base-posp-tagger | 4dfd27bb9efb1e847ac107c1186d0e62d6a793f6 | 2021-07-11T15:52:18.000Z | [
"pytorch",
"tf",
"roberta",
"token-classification",
"id",
"dataset:indonlu",
"arxiv:1907.11692",
"transformers",
"indonesian-roberta-base-posp-tagger",
"license:mit",
"autotrain_compatible"
] | token-classification | false | w11wo | null | w11wo/indonesian-roberta-base-posp-tagger | 119 | 1 | transformers | 4,343 | ---
language: id
tags:
- indonesian-roberta-base-posp-tagger
license: mit
datasets:
- indonlu
widget:
- text: "Budi sedang pergi ke pasar."
---
## Indonesian RoBERTa Base POSP Tagger
Indonesian RoBERTa Base POSP Tagger is a part-of-speech token-classification model based on the [RoBERTa](https://arxiv.org/abs/1... |
vumichien/tiny-albert | 48ab0d3d6f338494632dbd0abb54a8943376ab92 | 2022-04-14T00:16:10.000Z | [
"pytorch",
"tf",
"albert",
"token-classification",
"transformers",
"generated_from_keras_callback",
"model-index",
"autotrain_compatible"
] | token-classification | false | vumichien | null | vumichien/tiny-albert | 119 | null | transformers | 4,344 | ---
tags:
- generated_from_keras_callback
model-index:
- name: tiny-albert
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# tiny-albert
This model is a fine-tuned ve... |
nielsr/layoutlmv3-finetuned-cord | 1c8ca65840cb3c7b5fece0b1db5e5dfb90378987 | 2022-05-02T19:28:12.000Z | [
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"dataset:cord",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | nielsr | null | nielsr/layoutlmv3-finetuned-cord | 119 | 4 | transformers | 4,345 | ---
tags:
- generated_from_trainer
datasets:
- cord
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-cord
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cord
type: cord
args: cord
metrics:
- name:... |
IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Similarity | a684033e0020d1558c74913fd365855b0af819eb | 2022-05-16T06:07:29.000Z | [
"pytorch",
"megatron-bert",
"text-classification",
"zh",
"transformers",
"bert",
"NLU",
"NLI",
"license:apache-2.0"
] | text-classification | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Similarity | 119 | null | transformers | 4,346 | ---
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- NLI
inference: true
widget:
- text: "今天心情不好[SEP]今天很开心"
---
# Erlangshen-MegatronBert-1.3B-Similarity, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
We collect 20 paraphrace datasets in the Chinese domain ... |
PSW/samsum_reverse_train_distilbart_xsum_9-6_min10max2000_topp0.5_topk20_epoch3 | e8cb1aa6dd45eb26060714018a2a6fd6ee84068e | 2022-07-13T05:57:29.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | PSW | null | PSW/samsum_reverse_train_distilbart_xsum_9-6_min10max2000_topp0.5_topk20_epoch3 | 119 | null | transformers | 4,347 | Entry not found |
Thoumey/DialoGPT-small-Leksa | 4a6639ad1c44129132ab61babd1628dcc15785b5 | 2022-07-18T23:01:18.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Thoumey | null | Thoumey/DialoGPT-small-Leksa | 119 | null | transformers | 4,348 | ---
tags:
- conversational
---
|
kakife3586/Hmm | bfa2f5b803ebf859bedb4919d2b94e05712e48e7 | 2022-07-30T03:52:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | kakife3586 | null | kakife3586/Hmm | 119 | null | transformers | 4,349 | Entry not found |
Helsinki-NLP/opus-mt-es-ar | c2ccbc0ebc3356c9cee203736e228606b1a30b7c | 2021-01-18T08:21:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"ar",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-ar | 118 | null | transformers | 4,350 | ---
language:
- es
- ar
tags:
- translation
license: apache-2.0
---
### spa-ara
* source group: Spanish
* target group: Arabic
* OPUS readme: [spa-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-ara/README.md)
* model: transformer
* source language(s): spa
* target language(s): a... |
Helsinki-NLP/opus-mt-ja-de | 3bb459b05d07803d6c6d9681e84e60179157a796 | 2021-09-10T13:53:07.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-de | 118 | null | transformers | 4,351 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ja-de
* source languages: ja
* target languages: de
* OPUS readme: [ja-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ja-de/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
PlanTL-GOB-ES/roberta-base-bne-capitel-pos | 982306bac3ed69f0b207aa7efbfb0bc8570f0bc6 | 2022-04-06T14:41:41.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"pos",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/roberta-base-bne-capitel-pos | 118 | null | transformers | 4,352 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "capitel"
- "pos"
datasets:
- "bne"
- "capitel"
metrics:
- "f1"
widget:
- text: "Festival de San Sebastián: Johnny Depp recibirá el premio Donostia en pleno rifirrafe judicial con Amber Heard"
- text: "El alcalde de Vigo... |
Tanhim/translation-En2De | 075887a7adf00d27441f0b52f47d080aa94b5250 | 2021-09-30T10:08:21.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"dataset:wmt19",
"transformers",
"translation",
"license:gpl",
"autotrain_compatible"
] | translation | false | Tanhim | null | Tanhim/translation-En2De | 118 | 2 | transformers | 4,353 | ---
language: de
widget:
- text: My name is Karl and I live in Aachen.
tags:
- translation
datasets:
- wmt19
license: gpl
---
<h2> English to German Translation </h2>
Model Name: Tanhim/translation-En2De <br />
language: German or Deutsch <br />
thumbnail: https://huggingface.co/Tanhim/translation-En2De <br />
##... |
bakrianoo/t5-arabic-small | 2a44acb28d6fac20bb5420f60ea7774e9983150f | 2021-06-26T17:10:58.000Z | [
"pytorch",
"t5",
"text2text-generation",
"Arabic",
"dataset:mc4",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | bakrianoo | null | bakrianoo/t5-arabic-small | 118 | 1 | transformers | 4,354 | ---
language: Arabic
datasets:
- mc4
license: apache-2.0
---
## Arabic T5 Small Model
A customized T5 Model for Arabic and English Task. It could be used as an alternative for `google/mt5-small` model, as it's much smaller and only targets Arabic and English based tasks.
### About T5
```
T5 is an encoder-decoder mo... |
csarron/mobilebert-uncased-squad-v2 | 153e4767e7c96f8d3a1d705afada1ca1d4c2bf11 | 2020-12-11T21:36:27.000Z | [
"pytorch",
"mobilebert",
"question-answering",
"en",
"dataset:squad_v2",
"arxiv:2004.02984",
"transformers",
"license:mit",
"autotrain_compatible"
] | question-answering | false | csarron | null | csarron/mobilebert-uncased-squad-v2 | 118 | null | transformers | 4,355 | ---
language: en
thumbnail:
license: mit
tags:
- question-answering
- mobilebert
datasets:
- squad_v2
metrics:
- squad_v2
widget:
- text: "Which name is also used to describe the Amazon rainforest in English?"
context: "The Amazon rainforest (Portuguese: Floresta Amazônica or Amazônia; Spanish: Selva Amazónica, Amaz... |
dmis-lab/biosyn-sapbert-ncbi-disease | 129c7b75ed6dd9c3c390e819450fe47569eae6aa | 2021-10-25T14:44:57.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | dmis-lab | null | dmis-lab/biosyn-sapbert-ncbi-disease | 118 | null | transformers | 4,356 | Entry not found |
google/t5-efficient-tiny-nl32 | f8f8d94dccb6781faf8809f6f636c1688f266c23 | 2022-02-15T10:51:44.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2109.10686",
"transformers",
"deep-narrow",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-efficient-tiny-nl32 | 118 | 2 | transformers | 4,357 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-TINY-NL32 (Deep-Narrow version)
T5-Efficient-TINY-NL32 is a variation of [Google's original T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) following the [T5 model architectur... |
hfl/chinese-electra-180g-small-generator | 1eaae8e9a46729e458014614eedd62b1de383d48 | 2021-03-03T01:23:58.000Z | [
"pytorch",
"tf",
"electra",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0",
"fill-mask"
] | fill-mask | false | hfl | null | hfl/chinese-electra-180g-small-generator | 118 | 2 | transformers | 4,358 | ---
language:
- zh
license: "apache-2.0"
pipeline_tag: "fill-mask"
---
# This model is trained on 180G data, we recommend using this one than the original version.
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively com... |
m3hrdadfi/gpt2-QA | 78ef9368b2a2ff9a0993598798fc0e08800a5d70 | 2021-08-11T11:26:26.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"en",
"dataset:squad",
"transformers"
] | text-generation | false | m3hrdadfi | null | m3hrdadfi/gpt2-QA | 118 | null | transformers | 4,359 | ---
language: en
datasets:
- squad
tags:
- text-generation
---
# GPT2 QA
Using GPT2 in other downstream NLP tasks like QA. The model was trained and evaluated on [squad](https://huggingface.co/datasets/squad).
## Dataset
- [squad](https://huggingface.co/datasets/squad)
## Evaluation
The following table summarizes t... |
nicoladecao/msmarco-word2vec256000-bert-base-uncased | 79cba49408c0f63e3ffea9f123829988578e6024 | 2022-02-17T17:58:46.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers",
"license:mit"
] | feature-extraction | false | nicoladecao | null | nicoladecao/msmarco-word2vec256000-bert-base-uncased | 118 | null | transformers | 4,360 | ---
license: mit
---
|
ckiplab/bert-base-han-chinese-ws | 7b436d9e9dc36cf8f34ca8704cb2eb6676ac350c | 2022-07-04T08:06:59.000Z | [
"pytorch",
"bert",
"token-classification",
"zh",
"transformers",
"license:gpl-3.0",
"autotrain_compatible"
] | token-classification | false | ckiplab | null | ckiplab/bert-base-han-chinese-ws | 118 | null | transformers | 4,361 | ---
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 Han Chinese WS
This model provides word segmentation for the ancient Chinese language. Our training dataset covers four eras of the Chines... |
RonEliav/QA_discourse_v2 | ac6093e514dadbcf41b7158b8efc513d1ab5db52 | 2022-07-07T19:40:33.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | RonEliav | null | RonEliav/QA_discourse_v2 | 118 | null | transformers | 4,362 | ---
license: afl-3.0
---
|
CuongLD/wav2vec2-large-xlsr-vietnamese | 18c314ebda97c6fe6908c7138c7f571196b1cc7e | 2021-07-05T14:17:01.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:common_voice, infore_25h",
"arxiv:2006.11477",
"arxiv:2006.13979",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | CuongLD | null | CuongLD/wav2vec2-large-xlsr-vietnamese | 117 | null | transformers | 4,363 | ---
language: vi
datasets:
- common_voice, infore_25h
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Cuong-Cong XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
Helsinki-NLP/opus-mt-en-tl | f7e0d3952dd506aefb67c1346651a17586b0ed5b | 2021-09-09T21:39:50.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"tl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-tl | 117 | null | transformers | 4,364 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-tl
* source languages: en
* target languages: tl
* OPUS readme: [en-tl](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-tl/README.md)
* dataset: opus+bt
* model: transformer-align
* pre-processing: normalization + SentencePiece
* do... |
bertin-project/bertin-base-ner-conll2002-es | 602bfb92e668c2f02ceb09a531d4ab2b98dfab30 | 2021-09-23T13:41:49.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"transformers",
"spanish",
"ner",
"license:cc-by-4.0",
"autotrain_compatible"
] | token-classification | false | bertin-project | null | bertin-project/bertin-base-ner-conll2002-es | 117 | 1 | transformers | 4,365 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
- ner
---
This checkpoint has been trained for the NER task using the CoNLL2002-es dataset.
This is a NER checkpoint created from **Bertin Gaussian 512**, which is a **RoBERTa-base** model trained from scratch in Spanish. Information on this base model may... |
flax-community/papuGaPT2-large | be2735b4d7369f415c2bf51c653c685fa8e57140 | 2021-07-17T09:02:00.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | flax-community | null | flax-community/papuGaPT2-large | 117 | 2 | transformers | 4,366 | Entry not found |
textattack/xlnet-base-cased-MNLI | 0e139049908482a348433a901ac078cee10b6ca6 | 2020-06-09T16:55:37.000Z | [
"pytorch",
"xlnet",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/xlnet-base-cased-MNLI | 117 | 1 | transformers | 4,367 | Entry not found |
ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli | d3f76223398627895574663d5a446c640fbf776a | 2020-10-17T02:00:30.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers"
] | text-classification | false | ynie | null | ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli | 117 | null | transformers | 4,368 | Entry not found |
brad1141/Longformer-finetuned-norm | 0330a84ed4c303bf8f2c63dd7b4618c7c22d2a17 | 2022-03-18T05:42:11.000Z | [
"pytorch",
"tensorboard",
"longformer",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | brad1141 | null | brad1141/Longformer-finetuned-norm | 117 | null | transformers | 4,369 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Longformer-finetuned-norm
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... |
HannahRoseKirk/Hatemoji | f2f98581ab15fb3ccf8b8a5465d7ca70c2958902 | 2022-04-27T18:17:04.000Z | [
"pytorch",
"deberta",
"text-classification",
"en",
"dataset:HatemojiBuild",
"dataset:HatemojiCheck",
"arxiv:2108.05921",
"arxiv:2012.15761",
"arxiv:2202.11176",
"transformers",
"hate-speech-detection",
"license:cc-by-4.0"
] | text-classification | false | HannahRoseKirk | null | HannahRoseKirk/Hatemoji | 117 | 2 | transformers | 4,370 | ---
license: cc-by-4.0
language:
- en
tags:
- text-classification
- pytorch
- hate-speech-detection
datasets:
- HatemojiBuild
- HatemojiCheck
metrics:
- Accuracy, F1 Score
---
# Hatemoji Model
## Model description
This model is a fine-tuned version of the [DeBERTa base model](https://huggingface.co/microsoft/debert... |
emilylearning/added_birth_date__test_run_False__p_dataset_100 | 913dfca69757e298098698ba5691c5833f3f4b0c | 2022-05-06T07:21:37.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | emilylearning | null | emilylearning/added_birth_date__test_run_False__p_dataset_100 | 117 | null | transformers | 4,371 | Entry not found |
BigSalmon/InformalToFormalLincoln59Paraphrase | ae656e0df5f65d72b84eb2692235fac71088a10e | 2022-07-30T02:35:10.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | BigSalmon | null | BigSalmon/InformalToFormalLincoln59Paraphrase | 117 | null | transformers | 4,372 | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln59Paraphrase")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln59Paraphrase")
```
```
How To Make Prompt:
informal english: i am very ready to do... |
Helsinki-NLP/opus-mt-wa-en | 28ebf552f45eeed983142aefd3748c188519ec00 | 2021-09-11T10:51:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"wa",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-wa-en | 116 | null | transformers | 4,373 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-wa-en
* source languages: wa
* target languages: en
* OPUS readme: [wa-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/wa-en/README.md)
* dataset: opus-enwa
* model: transformer
* pre-processing: normalization + SentencePiece
* downlo... |
dehio/german-qg-t5-e2e-quad | 4cfad838612aebf0f2a17ab07b435cce4c3aea70 | 2022-01-20T09:40:47.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"de",
"dataset:deepset/germanquad",
"transformers",
"question generation",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | dehio | null | dehio/german-qg-t5-e2e-quad | 116 | 1 | transformers | 4,374 | ---
license: mit
widget:
- text: "Naturschutzwarte haben auf der ostfriesischen Insel Wangerooge zwei seltene Kurzschnäuzige Seepferdchen entdeckt. Die Tiere seien vergangene Woche bei einer sogenannten Spülsaumkontrolle entdeckt worden, bei der die Strände eigentlich nach Müll und toten Vögeln abgesucht würden, sagte ... |
geralt/MechDistilGPT2 | 4aad2e706976210172b6389fdf8cadb41987fca7 | 2021-08-13T12:54:31.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | geralt | null | geralt/MechDistilGPT2 | 116 | null | transformers | 4,375 | \n---
tags:
- Causal Language modeling
- text-generation
- CLM
model_index:
- name: MechDistilGPT2
results:
- task:
name: Causal Language modeling
type: Causal Language modeling
---
## MechDistilGPT2
This model is fine-tuned on text scraped from 100+ Mechanical/Automotive pdf books.
Base model is Disti... |
gmihaila/wav2vec2-large-xlsr-53-romanian | 9d42a534870eaa11ddbc772b01ad781042d8ce53 | 2021-07-06T05:34:33.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ro",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | gmihaila | null | gmihaila/wav2vec2-large-xlsr-53-romanian | 116 | null | transformers | 4,376 | ---
language: ro
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Romanian by George Mihaila
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name:... |
readerbench/jurBERT-base | 124190766a0ac585ae80e2b8c3d5cdf09ef889fc | 2021-11-19T11:56:10.000Z | [
"pytorch",
"tf",
"bert",
"ro",
"transformers"
] | null | false | readerbench | null | readerbench/jurBERT-base | 116 | null | transformers | 4,377 | Model card for jurBERT-base
---
language:
- ro
---
# jurBERT-base
## Pretrained juridical BERT model for Romanian
BERT Romanian juridical model trained using a masked language modeling (MLM) and next sentence prediction (NSP) objective.
It was introduced in this [paper](https://aclanthology.org/2021.nllp-1.8/).... |
sgugger/resnet50d | 4b32487424f0f5f2f17ffb60d578b8e5ac7ddc35 | 2021-11-03T16:22:16.000Z | [
"pytorch",
"dataset:imagenet",
"arxiv:1512.03385",
"arxiv:1812.01187",
"arxiv:1906.02659",
"arxiv:2010.15052",
"timm",
"image-classification",
"resnet",
"license:apache-2.0"
] | image-classification | false | sgugger | null | sgugger/resnet50d | 116 | 3 | timm | 4,378 | ---
tags:
- image-classification
- timm
- resnet
license: apache-2.0
datasets:
- imagenet
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: h... |
vblagoje/dpr-question_encoder-single-lfqa-base | fd2656c623ec5b21fc764de1e4e97f0f50ba7f07 | 2022-03-11T10:11:54.000Z | [
"pytorch",
"dpr",
"feature-extraction",
"en",
"dataset:vblagoje/lfqa",
"transformers",
"license:mit"
] | feature-extraction | false | vblagoje | null | vblagoje/dpr-question_encoder-single-lfqa-base | 116 | null | transformers | 4,379 | ---
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.
##... |
luyaojie/uie-large-en | 458a7066e8d6217b25945fe71f04f375910e8487 | 2022-04-19T10:14:55.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | luyaojie | null | luyaojie/uie-large-en | 116 | null | transformers | 4,380 | ---
license: cc-by-nc-sa-4.0
---
|
demdecuong/vihealthbert-base-word | f89e80b461e86f9cfc1c84019bd819830c24b6c5 | 2022-04-20T07:55:52.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | demdecuong | null | demdecuong/vihealthbert-base-word | 116 | 2 | transformers | 4,381 | # <a name="introduction"></a> ViHealthBERT: Pre-trained Language Models for Vietnamese in Health Text Mining
ViHealthBERT is the a strong baseline language models for Vietnamese in Healthcare domain.
We empirically investigate our model with different training strategies, achieving state of the art (SOTA) performa... |
lucataco/DialoGPT-medium-milo | 3d03b0782381cf6e818779f6e8bc5d03d6d9f355 | 2022-07-03T23:35:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | lucataco | null | lucataco/DialoGPT-medium-milo | 116 | null | transformers | 4,382 | ---
tags:
- conversational
---
# Milo Dialog GPT Model Medium 12
# Trained on discord channels:
# half of Dragalia chat |
lbox/lcube-base | 6b69fc2a4f4574ff9fb761dd5b17409edf185c83 | 2022-06-17T02:10:42.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | lbox | null | lbox/lcube-base | 116 | null | transformers | 4,383 | ## How to use
```python
import transformers
model = transformers.GPT2LMHeadModel.from_pretrained("lbox/lcube-base")
tokenizer = transformers.AutoTokenizer.from_pretrained(
"lbox/lcube-base",
bos_token="[BOS]",
unk_token="[UNK]",
pad_token="[PAD]",
mask_token="[MASK]",
)
text = "피고인은 불상지에 있는 커피숍에서... |
inywer/2-0OKUOHS | c9e02e0c98fa1493fa42baba8ba9dd952762ec6d | 2022-07-10T22:43:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | inywer | null | inywer/2-0OKUOHS | 116 | null | transformers | 4,384 | ---
tags:
- conversational
---
# inywer/2-0OKUOHS Model |
seegene/viral-sixmerta-small2 | e1085c057bca9a062f0624be90f932fc34c0516c | 2022-07-29T00:09:38.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | seegene | null | seegene/viral-sixmerta-small2 | 116 | null | transformers | 4,385 | ---
license: apache-2.0
widget:
- text: "AAGCGAGACGACTTTTACGC<MASK>GGATAGCTAGGCTAGCATCG"
example_title: "Mutation Probability"
---
# Viral-RoBERTa-small
- NCBI Virus 서열을 언어 모델에 사전학습 (짧은 길이의 서열 비율 증가)
- 6-mer word level 에서 Byte Pair Encoding (BPE) 토크나이저 사용 (빈도수 20으로 vocab 제작)
- RoBERTa architecture 기반 사전학습 진행, transfo... |
Helsinki-NLP/opus-mt-en-mr | 85463bb8620cf8685e6323252cb24d7d819f3afc | 2021-09-09T21:37:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"mr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-mr | 115 | 1 | transformers | 4,386 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-mr
* source languages: en
* target languages: mr
* OPUS readme: [en-mr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-mr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-pl-fr | a23ffba6953bea7606d7abbd47215dcd58d331ea | 2021-09-10T14:01:23.000Z | [
"pytorch",
"marian",
"text2text-generation",
"pl",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-pl-fr | 115 | null | transformers | 4,387 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-pl-fr
* source languages: pl
* target languages: fr
* OPUS readme: [pl-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/pl-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ru-uk | db108c722752b88d9717193bce732737a1afb00f | 2020-08-21T14:42:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ru",
"uk",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ru-uk | 115 | 1 | transformers | 4,388 | ---
language:
- ru
- uk
tags:
- translation
license: apache-2.0
---
### rus-ukr
* source group: Russian
* target group: Ukrainian
* OPUS readme: [rus-ukr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/rus-ukr/README.md)
* model: transformer-align
* source language(s): rus
* target langu... |
SEBIS/code_trans_t5_small_commit_generation_transfer_learning_finetune | be1097115c98a0c67209a4184af241126e024dec | 2021-06-23T10:15:54.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_small_commit_generation_transfer_learning_finetune | 115 | null | transformers | 4,389 | ---
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 small model architecture. It was fir... |
dhimskyy/wiki-bert | d30ba6eb1dd857f3e365f3067a0fd425e904ce81 | 2021-05-19T15:41:20.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dhimskyy | null | dhimskyy/wiki-bert | 115 | null | transformers | 4,390 | Entry not found |
huggingtweets/dril | 15767121a74a84ae3403af3f60060ec4829cca4e | 2022-06-16T16:14:18.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/dril | 115 | 1 | transformers | 4,391 | ---
language: en
thumbnail: http://www.huggingtweets.com/dril/1655396053530/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; margin-right: 4px; width: 92p... |
laxya007/gpt2_BSA_Legal_Initiproject_OE_OS_BRM | 92f2c1caf732e5292beecd8a03559a288a23c404 | 2021-10-23T10:51:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | laxya007 | null | laxya007/gpt2_BSA_Legal_Initiproject_OE_OS_BRM | 115 | null | transformers | 4,392 | Entry not found |
liaad/srl-en_xlmr-base | 55387c653aba11f0025a2f7089435c11c4c583f6 | 2021-09-22T08:56:11.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"multilingual",
"pt",
"en",
"dataset:PropBank.Br",
"dataset:CoNLL-2012",
"arxiv:2101.01213",
"transformers",
"xlm-roberta-base",
"semantic role labeling",
"finetuned",
"license:apache-2.0"
] | feature-extraction | false | liaad | null | liaad/srl-en_xlmr-base | 115 | 1 | transformers | 4,393 | ---
language:
- multilingual
- pt
- en
tags:
- xlm-roberta-base
- semantic role labeling
- finetuned
license: apache-2.0
datasets:
- PropBank.Br
- CoNLL-2012
metrics:
- F1 Measure
---
# XLM-R base fine-tuned on English semantic role labeling
## Model description
This model is the [`xlm-roberta-base`](https://h... |
nateraw/tiny-vit-random | f0939d8baaaf0c86aa0240b31f8f63a6de8a38db | 2021-10-01T06:27:57.000Z | [
"pytorch",
"vit",
"feature-extraction",
"transformers"
] | feature-extraction | false | nateraw | null | nateraw/tiny-vit-random | 115 | null | transformers | 4,394 | Entry not found |
sciarrilli/biobert-base-cased-v1.2-finetuned-ner | 43e59ea29438545feddab3855d5b8161a7140b4a | 2021-10-15T21:47:28.000Z | [
"pytorch",
"bert",
"token-classification",
"dataset:jnlpba",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | sciarrilli | null | sciarrilli/biobert-base-cased-v1.2-finetuned-ner | 115 | null | transformers | 4,395 | ---
tags:
- generated_from_trainer
datasets:
- jnlpba
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biobert-base-cased-v1.2-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: jnlpba
type: jnlpba
args: jnlpba
... |
questgen/paraphrase-multilingual-mpnet-base-v2-feature-extraction-pipeline | fc186318516b8a7db7f6ae9e776f5f2210af88e9 | 2022-05-14T10:23:10.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | questgen | null | questgen/paraphrase-multilingual-mpnet-base-v2-feature-extraction-pipeline | 115 | null | sentence-transformers | 4,396 | ---
pipeline_tag: feature-extraction
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-multilingual-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dim... |
Helsinki-NLP/opus-mt-gaa-en | c5297321fb6cc0a2af0d953c89990382d5a6ffa8 | 2021-09-09T21:58:41.000Z | [
"pytorch",
"marian",
"text2text-generation",
"gaa",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-gaa-en | 114 | null | transformers | 4,397 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-gaa-en
* source languages: gaa
* target languages: en
* OPUS readme: [gaa-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/gaa-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
allenai/longformer-base-4096-extra.pos.embd.only | 16a4bb5ac90bac2c19c561cc0dda1bb9b1270da6 | 2021-03-10T02:32:23.000Z | [
"pytorch",
"tf",
"longformer",
"arxiv:2004.05150",
"transformers"
] | null | false | allenai | null | allenai/longformer-base-4096-extra.pos.embd.only | 114 | null | transformers | 4,398 |
# longformer-base-4096-extra.pos.embd.only
This model is similar to `longformer-base-4096` but it was pretrained to preserve RoBERTa weights by freezing all RoBERTa weights and only train the additional position embeddings.
### Citing
If you use `Longformer` in your research, please cite [Longformer: The Long-Doc... |
allenai/unifiedqa-v2-t5-base-1251000 | 344cc3377d51a92e7960cd7bd525a50975015c81 | 2022-02-22T00:26:37.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-v2-t5-base-1251000 | 114 | null | transformers | 4,399 | # Further details: https://github.com/allenai/unifiedqa |
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