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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
razent/SciFive-base-Pubmed_PMC | e26bb9e7ebd7cbaa196be47e9e1f28348f8aa434 | 2022-03-20T17:46:59.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:pubmed",
"dataset:pmc/open_access",
"arxiv:2106.03598",
"transformers",
"token-classification",
"text-classification",
"question-answering",
"text-generation",
"autotrain_compatible"
] | text-classification | false | razent | null | razent/SciFive-base-Pubmed_PMC | 735 | 1 | transformers | 2,000 | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
- pmc/open_access
---
# SciFive Pubmed+PMC Base
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs... |
NinaErlacher/distilroberta-base-climate-f-finetuned-squad_v2 | cb79290c354e432eca24d2e4726d2dd53c4e575f | 2022-06-17T12:07:56.000Z | [
"pytorch",
"tensorboard",
"roberta",
"question-answering",
"dataset:squad_v2",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | NinaErlacher | null | NinaErlacher/distilroberta-base-climate-f-finetuned-squad_v2 | 735 | null | transformers | 2,001 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: distilroberta-base-climate-f-finetuned-squad_v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... |
trueto/medbert-base-chinese | 668ca1e929abd0380c7ff831615b154122daf5c1 | 2021-05-20T08:08:47.000Z | [
"pytorch",
"jax",
"bert",
"pretraining",
"transformers"
] | null | false | trueto | null | trueto/medbert-base-chinese | 734 | 2 | transformers | 2,002 | # [medbert](https://github.com/trueto/medbert)
本项目开源硕士毕业论文“BERT模型在中文临床自然语言处理中的应用探索与研究”相关模型
## 评估基准
构建了中文电子病历命名实体识别数据集（CEMRNER）、中文医学文本命名实体识别数据集（CMTNER）、
中文医学问句-问句识别数据集（CMedQQ）和中文临床文本分类数据集（CCTC）。
| **数据集** | **训练集** | **验证集** | **测试集** | **任务类型** | **语料来源** |
| ---- | ---- | ---- |---- |---- |:----:|
| CE... |
IDEA-CCNL/Erlangshen-Ubert-110M-Chinese | d0257027b0a2190d9e74a019587ecea958f62772 | 2022-07-02T13:41:04.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"transformers",
"NLU",
"Sentiment",
"Chinese",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-Ubert-110M-Chinese | 733 | null | transformers | 2,003 | ---
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- Sentiment
- Chinese
inference: false
widget:
- text: "今天心情不好"
---
# Erlangshen-Ubert-110M, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM/tree/dev/yangping/fengshen/examples/ubert).
We collect 70+ datasets in... |
cointegrated/rut5-base-absum | c9b878be0a5030d7d08eeae6c832aac1221d9fd1 | 2021-11-12T10:52:26.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ru",
"dataset:IlyaGusev/gazeta",
"dataset:csebuetnlp/xlsum",
"dataset:mlsum",
"dataset:wiki_lingua",
"transformers",
"russian",
"summarization",
"license:mit",
"autotrain_compatible"
] | summarization | false | cointegrated | null | cointegrated/rut5-base-absum | 731 | 1 | transformers | 2,004 | ---
language: ["ru"]
tags:
- russian
- summarization
datasets:
- IlyaGusev/gazeta
- csebuetnlp/xlsum
- mlsum
- wiki_lingua
license: mit
widget:
- text: "Высота башни составляет 324 метра (1063 фута), примерно такая же высота, как у 81-этажного здания, и самое высокое сооружение в Париже. Его основание квадратно, размер... |
facebook/wav2vec2-large-xlsr-53-italian | e2760fe9ade861421db16f4548f6c0d48568ae0c | 2021-07-06T02:53:33.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:common_voice",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-large-xlsr-53-italian | 731 | 2 | transformers | 2,005 | ---
language: it
datasets:
- common_voice
tags:
- speech
- audio
- automatic-speech-recognition
license: apache-2.0
---
## Evaluation on Common Voice IT Test
```python
import torchaudio
from datasets import load_dataset, load_metric
from transformers import (
Wav2Vec2ForCTC,
Wav2Vec2Processor,
)
import torch
i... |
nvidia/groupvit-gcc-yfcc | fd613a6633497e83b16be6ddba17644151c44218 | 2022-06-29T07:21:09.000Z | [
"pytorch",
"groupvit",
"feature-extraction",
"arxiv:2202.11094",
"transformers",
"vision"
] | feature-extraction | false | nvidia | null | nvidia/groupvit-gcc-yfcc | 731 | null | transformers | 2,006 | ---
tags:
- vision
---
# Model Card: GroupViT
This checkpoint is uploaded by Jiarui Xu.
## Model Details
The GroupViT model was proposed in [GroupViT: Semantic Segmentation Emerges from Text Supervision](https://arxiv.org/abs/2202.11094) by Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan K... |
xlm-mlm-enfr-1024 | 31a5a94400075535209e7c1ebc8b01933543b2df | 2022-07-22T08:08:19.000Z | [
"pytorch",
"tf",
"xlm",
"fill-mask",
"multilingual",
"en",
"fr",
"arxiv:1901.07291",
"arxiv:1910.09700",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | fill-mask | false | null | null | xlm-mlm-enfr-1024 | 730 | null | transformers | 2,007 | ---
language:
- multilingual
- en
- fr
license: cc-by-nc-4.0
---
# xlm-mlm-enfr-1024
# Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Bias, Risks, and Limitations](#bias-risks-and-limitations)
4. [Training](#training)
5. [Evaluation](#evaluation)
6. [Environmental Impact](#environmental... |
allenai/hvila-row-layoutlm-finetuned-docbank | c01e12d0b0f90b91e155a89f53b7c7e2b65be943 | 2021-09-27T22:58:30.000Z | [
"pytorch",
"hierarchical_model",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | allenai | null | allenai/hvila-row-layoutlm-finetuned-docbank | 730 | null | transformers | 2,008 | Entry not found |
patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm | 5569ff8b50dc9207760d321264a6dfd18ee4324f | 2021-12-10T15:49:13.000Z | [
"pytorch",
"tf",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-large-xlsr-53-spanish-with-lm | 729 | 7 | transformers | 2,009 | ---
language: es
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
---
# Wav2Vec2-Large-XLSR-53-Spanish-With-LM
This is a model copy of [Wav2Vec2-Large-XLSR-53-Spanish](https://huggingface.co/jonatasgrosman/wav2vec2-large-xl... |
tanapatentlm/patentdeberta_base_spec_1024_pwi | 74f06791080deb3b9311f9be366f49af102ddf0a | 2022-06-17T06:08:37.000Z | [
"pytorch",
"deberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | tanapatentlm | null | tanapatentlm/patentdeberta_base_spec_1024_pwi | 729 | null | transformers | 2,010 | Entry not found |
Elron/bleurt-large-512 | 00397b0917e464c5ca1a45db156d0b836cd65e97 | 2021-12-15T01:57:26.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Elron | null | Elron/bleurt-large-512 | 728 | 1 | transformers | 2,011 | ## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](https:... |
jcblaise/electra-tagalog-small-uncased-discriminator | 2ca8fe4e593cd03e416e4c91460c92e6fb95bbd1 | 2021-11-12T03:24:06.000Z | [
"pytorch",
"electra",
"pretraining",
"tl",
"transformers",
"tagalog",
"filipino",
"license:gpl-3.0"
] | null | false | jcblaise | null | jcblaise/electra-tagalog-small-uncased-discriminator | 728 | null | transformers | 2,012 | ---
language: tl
tags:
- electra
- tagalog
- filipino
license: gpl-3.0
inference: false
---
**Deprecation Notice**
This model is deprecated. New Filipino Transformer models trained with a much larger corpora are available.
Use [`jcblaise/roberta-tagalog-base`](https://huggingface.co/jcblaise/roberta-tagalog-base) ... |
asafaya/bert-mini-arabic | 52baeaf85fd27116a23bbf1ab49ecfa5a1a9179b | 2021-05-19T11:48:07.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"dataset:oscar",
"dataset:wikipedia",
"transformers",
"autotrain_compatible"
] | fill-mask | false | asafaya | null | asafaya/bert-mini-arabic | 725 | null | transformers | 2,013 | ---
language: ar
datasets:
- oscar
- wikipedia
---
# Arabic BERT Mini Model
Pretrained BERT Mini language model for Arabic
_If you use this model in your work, please cite this paper:_
```
@inproceedings{safaya-etal-2020-kuisail,
title = "{KUISAIL} at {S}em{E}val-2020 Task 12: {BERT}-{CNN} for Offensive Speech ... |
cmarkea/distilcamembert-base-nli | df95b0550f822191f0b92bada34238e34d74ff16 | 2022-05-24T15:55:17.000Z | [
"pytorch",
"tf",
"camembert",
"text-classification",
"fr",
"dataset:flue",
"transformers",
"zero-shot-classification",
"sentence-similarity",
"nli",
"license:mit"
] | zero-shot-classification | false | cmarkea | null | cmarkea/distilcamembert-base-nli | 725 | 6 | transformers | 2,014 | ---
language: fr
license: mit
tags:
- zero-shot-classification
- sentence-similarity
- nli
pipeline_tag: zero-shot-classification
widget:
- text: "Selon certains physiciens, un univers parallèle, miroir du nôtre ou relevant de ce que l'on appelle la théorie des branes, autoriserait des neutrons à sortir de notre Unive... |
jonatasgrosman/wav2vec2-xls-r-1b-german | aa70cbb9841c017ce0cb02f00e3006ca8c33d4f1 | 2022-07-27T23:39:22.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-xls-r-1b-german | 724 | 2 | transformers | 2,015 | ---
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- de
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R Wav2Vec2 German by Jonatas Grosman
results:
- task:
name: Automatic Speec... |
bioformers/bioformer-cased-v1.0-ncbi-disease | ae933b056e69818beabffb6bd797921c5d0cbe42 | 2021-10-19T07:40:17.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | bioformers | null | bioformers/bioformer-cased-v1.0-ncbi-disease | 723 | null | transformers | 2,016 | [bioformer-cased-v1.0](https://huggingface.co/bioformers/bioformer-cased-v1.0) fined-tuned on the [NCBI Disease](https://doi.org/10.1016/j.jbi.2013.12.006) dataset for 10 epochs. This fine-tuned model can be used for NER for diseases.
|
qarib/bert-base-qarib | b4d8b380e40be2e149cf56a8f8a5efa7f246253d | 2021-05-20T03:42:19.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"ar",
"dataset:arabic_billion_words",
"dataset:open_subtitles",
"dataset:twitter",
"arxiv:2102.10684",
"transformers",
"tf",
"QARiB",
"qarib",
"autotrain_compatible"
] | fill-mask | false | qarib | null | qarib/bert-base-qarib | 723 | 2 | transformers | 2,017 | ---
language: ar
tags:
- pytorch
- tf
- QARiB
- qarib
datasets:
- arabic_billion_words
- open_subtitles
- twitter
metrics:
- f1
widget:
- text: " شو عندكم يا [MASK] ."
---
# QARiB: QCRI Arabic and Dialectal BERT
## About QARiB
QCRI Arabic and Dialectal BERT (QARiB) model, was trained on a collection of ~ 420 Million... |
radiogroup-crits/wav2vec2-xls-r-1b-italian-doc4lm-5gram | 6abd91b5124ece5310d86439128eeee2dc5b6370 | 2022-06-15T09:31:26.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"speech",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | radiogroup-crits | null | radiogroup-crits/wav2vec2-xls-r-1b-italian-doc4lm-5gram | 722 | 1 | transformers | 2,018 | ---
language:
- it
license: apache-2.0
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- it
- mozilla-foundation/common_voice_8_0
- speech
- wav2vec2
model-index:
- name: XLS-R Wav2Vec2 Italian by radiogroup crits
results:
- task... |
aneuraz/awesome-align-with-co | 777756717e1fa9556e304d4d5db173ee386b9c16 | 2022-04-29T16:16:12.000Z | [
"pytorch",
"bert",
"fill-mask",
"de",
"fr",
"en",
"ro",
"zh",
"arxiv:2101.08231",
"transformers",
"sentence alignment",
"license:bsd-3-clause",
"autotrain_compatible"
] | fill-mask | false | aneuraz | null | aneuraz/awesome-align-with-co | 721 | 1 | transformers | 2,019 | ---
language:
- de
- fr
- en
- ro
- zh
thumbnail:
tags:
- sentence alignment
license: bsd-3-clause
---
# AWESOME: Aligning Word Embedding Spaces of Multilingual Encoders
This model comes from the following GitHub repository: [https://github.com/neulab/awesome-align](https://github.com/neulab/awesome-align... |
CAMeL-Lab/bert-base-arabic-camelbert-da-pos-msa | 4d1932e5966d609bac3ca0683ae9765da39a1764 | 2021-10-18T09:44:25.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-da-pos-msa | 720 | 1 | transformers | 2,020 | ---
language:
- ar
license: apache-2.0
widget:
- text: 'إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع'
---
# CAMeLBERT-DA POS-MSA Model
## Model description
**CAMeLBERT-DA POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-DA](https://hug... |
NbAiLab/nb-bert-base-mnli | 086be91a73fbf74acb762280730ce369b3b51758 | 2021-11-17T15:07:03.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"no",
"dataset:mnli",
"dataset:multi_nli",
"dataset:xnli",
"arxiv:1909.00161",
"transformers",
"nb-bert",
"zero-shot-classification",
"tensorflow",
"norwegian",
"license:cc-by-4.0"
] | zero-shot-classification | false | NbAiLab | null | NbAiLab/nb-bert-base-mnli | 720 | null | transformers | 2,021 | ---
language: no
license: cc-by-4.0
thumbnail: https://raw.githubusercontent.com/NBAiLab/notram/master/images/nblogo_2.png
pipeline_tag: zero-shot-classification
tags:
- nb-bert
- zero-shot-classification
- pytorch
- tensorflow
- norwegian
- bert
datasets:
- mnli
- multi_nli
- xnli
widget:
- example_title: Nyhetsartikk... |
bashar-talafha/multi-dialect-bert-base-arabic | f84ad96a07fa1aa6ba176e6e1cea85c4105b663f | 2021-05-19T12:08:22.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"ar",
"dataset:nadi",
"arxiv:2007.05612",
"transformers",
"autotrain_compatible"
] | fill-mask | false | bashar-talafha | null | bashar-talafha/multi-dialect-bert-base-arabic | 720 | 3 | transformers | 2,022 | ---
language: ar
thumbnail: https://raw.githubusercontent.com/mawdoo3/Multi-dialect-Arabic-BERT/master/multidialct_arabic_bert.png
datasets:
- nadi
---
# Multi-dialect-Arabic-BERT
This is a repository of Multi-dialect Arabic BERT model.
By [Mawdoo3-AI](https://ai.mawdoo3.com/).
<p align="center">
<br>
<img s... |
laboro-ai/distilbert-base-japanese | 9072f3bbae926fa5483f12909f5d107c7941ced1 | 2020-12-18T03:09:19.000Z | [
"pytorch",
"distilbert",
"ja",
"transformers",
"license:cc-by-nc-4.0"
] | null | false | laboro-ai | null | laboro-ai/distilbert-base-japanese | 720 | 1 | transformers | 2,023 | ---
language: ja
tags:
- distilbert
license: cc-by-nc-4.0
---
|
imthanhlv/gpt2news | 142f41d2b8c3b9fdfaf3f57eefa0035862edd5c7 | 2022-01-01T18:14:53.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"vi",
"transformers",
"gpt"
] | text-generation | false | imthanhlv | null | imthanhlv/gpt2news | 718 | 1 | transformers | 2,024 | ---
language: vi
tags:
- gpt
widget:
- text: "Hôm qua những nhà khoa học Mỹ đã phát hiện ra loài cá lợn"
---
### GPT 2 News
**Update 02 Jan 2022**: Fixed mismatch tokenizer and model.wte size
### BibTex
```
@article{thanh21gpt2news,
author = {Thanh V. Le},
title = {Pretrained GPT-2 on Vietnamese news},
journ... |
howey/roberta-large-qnli | aaa0c066fc55c5768a4c30d7cb72dc8595c839a2 | 2021-06-03T14:12:46.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | howey | null | howey/roberta-large-qnli | 717 | null | transformers | 2,025 | Entry not found |
howey/roberta-large-qqp | a4c6d6e56f6099795457ca305901fb8a79b0a180 | 2021-06-04T06:22:59.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | howey | null | howey/roberta-large-qqp | 717 | null | transformers | 2,026 | Entry not found |
sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-lng-aligned | 63cf16f26e9be7a0ef793e10fe54900c75111046 | 2022-06-15T22:19:18.000Z | [
"pytorch",
"tf",
"distilbert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-lng-aligned | 715 | 1 | sentence-transformers | 2,027 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-lng-aligned
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & par... |
Helsinki-NLP/opus-mt-sla-en | ad888a10d15c0cbe1e45b94c18e260fdc19035f7 | 2020-08-21T14:42:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"be",
"hr",
"mk",
"cs",
"ru",
"pl",
"bg",
"uk",
"sl",
"sla",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sla-en | 714 | 0 | transformers | 2,028 | ---
language:
- be
- hr
- mk
- cs
- ru
- pl
- bg
- uk
- sl
- sla
- en
tags:
- translation
license: apache-2.0
---
### sla-eng
* source group: Slavic languages
* target group: English
* OPUS readme: [sla-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/sla-eng/README.md)
* model: trans... |
deepmind/vision-perceiver-learned | e3d8bac358a9994ce2f0887fad97855ab6e14691 | 2021-12-13T09:25:29.000Z | [
"pytorch",
"perceiver",
"image-classification",
"dataset:imagenet",
"arxiv:2107.14795",
"transformers",
"license:apache-2.0"
] | image-classification | false | deepmind | null | deepmind/vision-perceiver-learned | 714 | 3 | transformers | 2,029 | ---
license: apache-2.0
tags:
datasets:
- imagenet
---
# Perceiver IO for vision (learned position embeddings)
Perceiver IO model pre-trained on ImageNet (14 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Perceiver IO: A General Architecture for Structured Inputs & Outputs](http... |
Helsinki-NLP/opus-mt-en-id | ed4f67aeeb72d0f4d672d0bf78b89da24ab7f68b | 2021-09-09T21:36:08.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"id",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-id | 713 | null | transformers | 2,030 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-id
* source languages: en
* target languages: id
* OPUS readme: [en-id](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-id/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
nfliu/scibert_basevocab_uncased | dea4d1eba23b45c9632dc06523eec6461216bdca | 2021-05-20T01:39:31.000Z | [
"pytorch",
"jax",
"bert",
"transformers"
] | null | false | nfliu | null | nfliu/scibert_basevocab_uncased | 711 | null | transformers | 2,031 | Entry not found |
superb/hubert-base-superb-er | bac0e14e92f7f9fd56671c5060e572e883cad667 | 2021-11-04T16:03:24.000Z | [
"pytorch",
"hubert",
"audio-classification",
"en",
"dataset:superb",
"arxiv:2105.01051",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | audio-classification | false | superb | null | superb/hubert-base-superb-er | 709 | 1 | transformers | 2,032 | ---
language: en
datasets:
- superb
tags:
- speech
- audio
- hubert
- audio-classification
license: apache-2.0
widget:
- example_title: IEMOCAP clip "happy"
src: https://cdn-media.huggingface.co/speech_samples/IEMOCAP_Ses01F_impro03_F013.wav
- example_title: IEMOCAP clip "neutral"
src: https://cdn-media.huggingface... |
IDEA-CCNL/Wenzhong-GPT2-110M | 2beda4458b97e07b4810da6367aa56d7f7d8744e | 2022-05-30T07:16:29.000Z | [
"pytorch",
"gpt2",
"text-generation",
"zh",
"transformers",
"generate",
"license:apache-2.0"
] | text-generation | false | IDEA-CCNL | null | IDEA-CCNL/Wenzhong-GPT2-110M | 709 | 2 | transformers | 2,033 | ---
language:
- zh
inference:
parameters:
temperature: 0.7
top_p: 0.6
repetition_penalty: 1.1
max_new_tokens: 128
num_return_sequences: 3
do_sample: true
license: apache-2.0
tags:
- generate
- gpt2
widget:
- 北京是中国的
- 西湖的景色
---
# Wenzhong-GPT2-110M model (chinese)，one model of [Fengshen... |
rohanrajpal/bert-base-codemixed-uncased-sentiment | 78474f5ba8a100d6a40d89dff8ef12be0918c74a | 2021-05-20T04:32:54.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"hi",
"en",
"dataset:SAIL 2017",
"transformers",
"codemix"
] | text-classification | false | rohanrajpal | null | rohanrajpal/bert-base-codemixed-uncased-sentiment | 708 | null | transformers | 2,034 | ---
language:
- hi
- en
tags:
- hi
- en
- codemix
datasets:
- SAIL 2017
---
# Model name
## Model description
I took a bert-base-multilingual-cased model from huggingface and finetuned it on SAIL 2017 dataset.
## Intended uses & limitations
#### How to use
```python
# You can include sample code which will be f... |
mrm8488/CodeBERTaPy | ef04d7213fb852b414cc248fcb5e6a54ffbc5521 | 2021-05-20T18:01:23.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"code",
"arxiv:1909.09436",
"transformers",
"autotrain_compatible"
] | fill-mask | false | mrm8488 | null | mrm8488/CodeBERTaPy | 707 | 2 | transformers | 2,035 | ---
language: code
thumbnail:
---
# CodeBERTaPy
CodeBERTaPy is a RoBERTa-like model trained on the [CodeSearchNet](https://github.blog/2019-09-26-introducing-the-codesearchnet-challenge/) dataset from GitHub for `python` by [Manuel Romero](https://twitter.com/mrm8488)
The **tokenizer** is a Byte-level BPE tokenizer ... |
redrussianarmy/gpt2-turkish-cased | d4f4bd09a081f08a61fd58efd6e5fd8c5ae60ebf | 2021-05-23T12:12:42.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"tr",
"transformers",
"turkish",
"gpt2-tr",
"gpt2-turkish"
] | text-generation | false | redrussianarmy | null | redrussianarmy/gpt2-turkish-cased | 707 | 2 | transformers | 2,036 | ---
language: "tr"
tags:
- turkish
- tr
- gpt2-tr
- gpt2-turkish
---
# 🇹🇷 Turkish GPT-2 Model
In this repository I release GPT-2 model, that was trained on various texts for Turkish.
The model is meant to be an entry point for fine-tuning on other texts.
## Training corpora
I used a Turkish corpora that is taken ... |
tals/roberta_python | f42b279d6af7dc85ab2cceb2f7f54b624326b547 | 2022-06-07T01:48:03.000Z | [
"pytorch",
"roberta",
"fill-mask",
"python",
"dataset:code_search_net",
"dataset:Fraser/python-lines",
"arxiv:2106.05784",
"transformers",
"code",
"masked-lm",
"autotrain_compatible"
] | fill-mask | false | tals | null | tals/roberta_python | 706 | null | transformers | 2,037 | # roberta_python
---
language: python
datasets:
- code_search_net
- Fraser/python-lines
tags:
- python
- code
- masked-lm
widget:
- text "assert 6 == sum([i for i in range(<mask>)])"
---
# Details
This is a roBERTa-base model trained on the python part of [CodeSearchNet](https://github.com/github/CodeSearchNet) and rea... |
vinvino02/glpn-kitti | 1284de728759c071a2077a77f86a6d90e960ec91 | 2022-04-14T11:52:40.000Z | [
"pytorch",
"glpn",
"arxiv:2201.07436",
"transformers",
"vision",
"depth-estimation",
"license:apache-2.0"
] | null | false | vinvino02 | null | vinvino02/glpn-kitti | 706 | null | transformers | 2,038 | ---
license: apache-2.0
tags:
- vision
- depth-estimation
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https://huggingface.co/datasets/m... |
nickmuchi/segformer-b4-finetuned-segments-sidewalk | a8ca92dc8795137a2c54e00ada2c4dbcdfa79be0 | 2022-03-21T07:32:43.000Z | [
"pytorch",
"tensorboard",
"segformer",
"dataset:segments/sidewalk-semantic",
"transformers",
"vision",
"image-segmentation",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-segmentation | false | nickmuchi | null | nickmuchi/segformer-b4-finetuned-segments-sidewalk | 706 | 1 | transformers | 2,039 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
- generated_from_trainer
widget:
- src: https://drive.google.com/uc?id=1-ae6Vtvs-fO1j0D2kxEDX4rKxRipda2j
example_title: Sidewalk with traffic
- src: https://drive.google.com/uc?id=1-dwxxF6LzbEvATr_mwvrAjot-DdBLAM4
example_title: Sidewalk with buildings
dat... |
voidful/albert_chinese_small | d99b52392f291fca5a7b8df972af38019a25ddf8 | 2021-08-03T05:06:47.000Z | [
"pytorch",
"albert",
"fill-mask",
"zh",
"transformers",
"autotrain_compatible"
] | fill-mask | false | voidful | null | voidful/albert_chinese_small | 704 | null | transformers | 2,040 | ---
language: zh
pipeline_tag: fill-mask
widget:
- text: "今天[MASK]情很好"
---
# albert_chinese_small
This a albert_chinese_small model from [brightmart/albert_zh project](https://github.com/brightmart/albert_zh), albert_small_google_zh model
converted by huggingface's [script](https://github.com/huggingface/transfor... |
jonatasgrosman/wav2vec2-large-xlsr-53-polish | de2e25d651a4cdcd690a6b39d6f7966e072ff9b2 | 2022-07-27T23:36:03.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"pl",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"transformers",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"lice... | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-large-xlsr-53-polish | 703 | 0 | transformers | 2,041 | ---
language: pl
license: apache-2.0
datasets:
- common_voice
- mozilla-foundation/common_voice_6_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- mozilla-foundation/common_voice_6_0
- pl
- robust-speech-event
- speech
- xlsr-fine-tuning-week
model-index:
- name: XLSR Wav2Vec2 ... |
KoboldAI/fairseq-dense-355M | 907f5296869e6553e325c67bffc15cafa2dcf68f | 2022-02-01T22:49:26.000Z | [
"pytorch",
"xglm",
"text-generation",
"transformers"
] | text-generation | false | KoboldAI | null | KoboldAI/fairseq-dense-355M | 701 | 2 | transformers | 2,042 | Entry not found |
jonatasgrosman/wav2vec2-large-xlsr-53-italian | a959a4f932bf7f4d6942ced49c98fc6366715eaf | 2022-07-27T23:37:11.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"it",
"dataset:common_voice",
"dataset:mozilla-foundation/common_voice_6_0",
"transformers",
"audio",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_6_0",
"robust-speech-event",
"speech",
"xlsr-fine-tuning-week",
"lice... | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-large-xlsr-53-italian | 701 | 5 | transformers | 2,043 | ---
language: it
license: apache-2.0
datasets:
- common_voice
- mozilla-foundation/common_voice_6_0
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- it
- mozilla-foundation/common_voice_6_0
- robust-speech-event
- speech
- xlsr-fine-tuning-week
model-index:
- name: XLSR Wav2Vec2 ... |
tscholak/1zha5ono | cb38df00e41169d44053dd24405d229856fdfb06 | 2022-01-10T21:50:11.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:spider",
"arxiv:2109.05093",
"transformers",
"text2sql",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | tscholak | null | tscholak/1zha5ono | 700 | null | transformers | 2,044 | ---
language:
- en
thumbnail: "https://repository-images.githubusercontent.com/401779782/c2f46be5-b74b-4620-ad64-57487be3b1ab"
tags:
- text2sql
widget:
- "How many singers do we have? | concert_singer | stadium : stadium_id, location, name, capacity, highest, lowest, average | singer : singer_id, name, country, song... |
yuchenlin/BART0pp | ea0d45ccae6e8b4a14c5ad2bb06f23ea871f5e7c | 2021-12-10T05:49:45.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:bigscience/P3",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | yuchenlin | null | yuchenlin/BART0pp | 700 | 5 | transformers | 2,045 | ---
datasets:
- bigscience/P3
language: en
license: apache-2.0
widget:
- text: "A is the son's of B's uncle. What is the family relationship between A and B?"
- text: "Reorder the words in this sentence: justin and name bieber years is my am I 27 old."
- text: "Task: copy but say the opposite.\n
PSG won its match again... |
tomh/toxigen_roberta | 0e65216a558feba4bb167d47e49f9a9e229de6ab | 2022-05-01T19:42:09.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"arxiv:2203.09509",
"transformers"
] | text-classification | false | tomh | null | tomh/toxigen_roberta | 699 | null | transformers | 2,046 | ---
language:
- en
tags:
- text-classification
---
Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, Ece Kamar.
This model comes from the paper [ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection](https://arxiv.org/abs/2203.09509) and can... |
gengp/gpt-2-komodoh | 22a3ad22afec32f08d5057cf74b3ee7057a6833c | 2022-06-17T17:06:22.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"license:gpl-3.0"
] | text-generation | false | gengp | null | gengp/gpt-2-komodoh | 699 | null | transformers | 2,047 | ---
license: gpl-3.0
---
|
hf-internal-testing/tiny-random-reformer | 92d3924b57fe38f8c03ad579f85e7c4b3614e804 | 2022-04-04T13:23:05.000Z | [
"pytorch",
"reformer",
"transformers"
] | null | false | hf-internal-testing | null | hf-internal-testing/tiny-random-reformer | 698 | null | transformers | 2,048 | Entry not found |
theainerd/Wav2Vec2-large-xlsr-hindi | abe6b3384821d1cc890f782c84e828883f3f3a3e | 2021-03-29T07:14:33.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hi",
"dataset:Interspeech 2021",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | theainerd | null | theainerd/Wav2Vec2-large-xlsr-hindi | 697 | 1 | transformers | 2,049 | ---
language: hi
datasets:
- Interspeech 2021
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Hindi by Shyam Sunder Kumar
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
hfl/chinese-xlnet-mid | e103afe9441e257b0d55b78fbe1015805f384edb | 2021-03-03T01:46:39.000Z | [
"pytorch",
"tf",
"xlnet",
"text-generation",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0"
] | text-generation | false | hfl | null | hfl/chinese-xlnet-mid | 695 | 4 | transformers | 2,050 | ---
language:
- zh
license: "apache-2.0"
---
## Chinese Pre-Trained XLNet
This project provides a XLNet pre-training model for Chinese, which aims to enrich Chinese natural language processing resources and provide a variety of Chinese pre-training model selection.
We welcome all experts and scholars to download and ... |
Helsinki-NLP/opus-mt-en-ur | aa89f9a5c095d34e13ed9a07be73357c6fc785c4 | 2021-01-18T08:18:58.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ur",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ur | 694 | 1 | transformers | 2,051 | ---
language:
- en
- ur
tags:
- translation
license: apache-2.0
---
### eng-urd
* source group: English
* target group: Urdu
* OPUS readme: [eng-urd](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-urd/README.md)
* model: transformer-align
* source language(s): eng
* target language(s... |
DaNLP/da-bert-emotion-classification | 500107b8f0b4ef43f2162dff0cd733631df14f4c | 2021-09-23T13:37:15.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"da",
"dataset:social media",
"transformers",
"emotion",
"license:cc-by-sa-4.0"
] | text-classification | false | DaNLP | null | DaNLP/da-bert-emotion-classification | 692 | 1 | transformers | 2,052 | ---
language:
- da
tags:
- bert
- pytorch
- emotion
license: cc-by-sa-4.0
datasets:
- social media
metrics:
- f1
widget:
- text: Jeg ejer en rød bil og det er en god bil.
---
# Danish BERT for emotion classification
The BERT Emotion model classifies a Danish text in one of the following class:
* Glæde/Sindsro
* Tilli... |
google/vit-huge-patch14-224-in21k | 274b0d6e8a17e6ea6436338480a0ad100623115f | 2022-01-28T10:24:44.000Z | [
"pytorch",
"tf",
"jax",
"vit",
"feature-extraction",
"dataset:imagenet-21k",
"arxiv:2010.11929",
"arxiv:2006.03677",
"transformers",
"vision",
"license:apache-2.0"
] | feature-extraction | false | google | null | google/vit-huge-patch14-224-in21k | 692 | 1 | transformers | 2,053 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet-21k
inference: false
---
# Vision Transformer (huge-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. It was introduced in the paper [An Image is Worth 16x16 Words: Transformer... |
snunlp/KR-ELECTRA-discriminator | efc5fd1b31c3213ad68e84b49a127b249281efcc | 2022-05-04T06:22:51.000Z | [
"pytorch",
"electra",
"pretraining",
"ko",
"transformers"
] | null | false | snunlp | null | snunlp/KR-ELECTRA-discriminator | 692 | null | transformers | 2,054 | ---
language:
- "ko"
---
## KoRean based ELECTRA (KR-ELECTRA)
This is a release of a Korean-specific ELECTRA model with comparable or better performances developed by the Computational Linguistics Lab at Seoul National University. Our model shows remarkable performances on tasks related to informal texts such as r... |
uer/gpt2-distil-chinese-cluecorpussmall | a74565bf920f47043b84b62d6444e4a55a74a574 | 2022-07-15T08:27:10.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"zh",
"dataset:CLUECorpusSmall",
"transformers"
] | text-generation | false | uer | null | uer/gpt2-distil-chinese-cluecorpussmall | 692 | 3 | transformers | 2,055 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "米饭是一种用稻米与水煮成的食物"
---
# Chinese GPT2-distil Model
## Model description
The model is used to generate Chinese texts. You can download the model either from the [GPT2-Chinese Github page](https://github.com/Morizeyao/GPT2-Chinese), or via HuggingFace from ... |
elozano/tweet_sentiment_eval | 76eddba683fc8f13d01a2068dadcea76f0edb0fd | 2022-02-07T17:50:59.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:tweet_eval",
"transformers",
"license:mit"
] | text-classification | false | elozano | null | elozano/tweet_sentiment_eval | 691 | 2 | transformers | 2,056 | ---
license: mit
datasets:
- tweet_eval
language: en
widget:
- text: "I love summer!"
example_title: "Positive"
- text: "Does anyone want to play?"
example_title: "Neutral"
- text: "This movie is just awful! 😫"
example_title: "Negative"
---
|
schen/longformer-chinese-base-4096 | f0e53c8afe22f6b7cca5d5278fda13e26951a3b6 | 2021-05-20T05:07:16.000Z | [
"pytorch",
"jax",
"bert",
"pretraining",
"transformers"
] | null | false | schen | null | schen/longformer-chinese-base-4096 | 689 | 4 | transformers | 2,057 | Entry not found |
speechbrain/m-ctc-t-large | ab27b818661fa5e07bd53eae8065c4bb7b671790 | 2022-06-05T15:41:09.000Z | [
"pytorch",
"mctct",
"automatic-speech-recognition",
"en",
"dataset:common_voice",
"dataset:voxpopuli",
"arxiv:2111.00161",
"transformers",
"speech",
"license:apache-2.0"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/m-ctc-t-large | 689 | 8 | transformers | 2,058 | ---
language: en
datasets:
- common_voice
- voxpopuli
multilinguality:
- multilingual
tags:
- speech
license: apache-2.0
---
# M-CTC-T
Massively multilingual speech recognizer from Meta AI. The model is a 1B-param transformer encoder, with a CTC head over 8065 character labels and a language identification head ove... |
manu/lilt-infoxlm-base | 8575dfa0e9ad599465896d09da012b2150d601e9 | 2022-03-30T14:47:15.000Z | [
"pytorch",
"liltrobertalike",
"fill-mask",
"es",
"fr",
"ru",
"en",
"it",
"dataset:iit-cdip",
"transformers",
"token-classification",
"license:mit",
"autotrain_compatible"
] | token-classification | false | manu | null | manu/lilt-infoxlm-base | 687 | 2 | transformers | 2,059 | ---
language:
- es
- fr
- ru
- en
- it
tags:
- token-classification
- fill-mask
license: mit
datasets:
- iit-cdip
---
This model is the pretrained infoxlm checkpoint from the paper "LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding".
Original repository: http... |
SEBIS/code_trans_t5_large_source_code_summarization_python_multitask_finetune | 368b888aa864b0546765fc126e70146e0458f8d8 | 2021-06-23T09:21:31.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_source_code_summarization_python_multitask_finetune | 684 | 2 | transformers | 2,060 | ---
tags:
- summarization
widget:
- text: '''with open ( CODE_STRING , CODE_STRING ) as in_file : buf = in_file . readlines ( ) with open ( CODE_STRING , CODE_STRING ) as out_file : for line in buf : if line == " ; Include this text " : line = line + " Include below " out_file . w... |
speechbrain/asr-transformer-transformerlm-librispeech | 586c7897e606d6a00f0513e1ae527a5824d10eac | 2022-06-05T15:55:26.000Z | [
"en",
"dataset:librispeech",
"arxiv:2106.04624",
"speechbrain",
"automatic-speech-recognition",
"CTC",
"Attention",
"Transformer",
"pytorch",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-transformer-transformerlm-librispeech | 681 | 3 | speechbrain | 2,061 | ---
language:
- en
thumbnail: null
tags:
- automatic-speech-recognition
- CTC
- Attention
- Transformer
- pytorch
- speechbrain
- hf-asr-leaderboard
license: apache-2.0
datasets:
- librispeech
metrics:
- wer
- cer
model-index:
- name: Transformer+TransformerLM by SpeechBrain
results:
- task:
name: Automatic S... |
uer/chinese_roberta_L-4_H-768 | 89a95a918d125753e32c32d2b9061455b1d4c5ac | 2022-07-15T08:12:40.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-4_H-768 | 681 | null | transformers | 2,062 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
PlanTL-GOB-ES/bsc-bio-ehr-es | 08d77ab94c269b7f7e53a6936b65b66434016af1 | 2022-04-11T11:02:25.000Z | [
"pytorch",
"roberta",
"fill-mask",
"es",
"transformers",
"biomedical",
"clinical",
"ehr",
"spanish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/bsc-bio-ehr-es | 680 | 3 | transformers | 2,063 | ---
language:
- es
tags:
- biomedical
- clinical
- ehr
- spanish
license: apache-2.0
metrics:
- ppl
widget:
- text: "El único antecedente personal a reseñar era la <mask> arterial."
- text: "Las radiologías óseas de cuerpo entero no detectan alteraciones <mask>, ni alteraciones vertebrales."
- text: "En el <mask> to... |
SEBIS/code_trans_t5_large_code_comment_generation_java_transfer_learning_finetune | 207a8be14efe3e07a84093ab914f655e09afedf6 | 2021-06-23T06:14:00.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers"
] | feature-extraction | false | SEBIS | null | SEBIS/code_trans_t5_large_code_comment_generation_java_transfer_learning_finetune | 678 | null | transformers | 2,064 | Entry not found |
google/bert_uncased_L-6_H-128_A-2 | cc3ddb10622cdf031e6c96cf314284cd788bc24b | 2021-05-19T17:33:17.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-6_H-128_A-2 | 678 | null | transformers | 2,065 | ---
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... |
sentence-transformers/use-cmlm-multilingual | 2528c966cf3b3d2e504d4209c8c688a63d77729f | 2022-06-15T20:44:55.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/use-cmlm-multilingual | 677 | 2 | sentence-transformers | 2,066 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
license: apache-2.0
---
# use-cmlm-multilingual
This is a pytorch version of the [universal-sentence-encoder-cmlm/multilingual-base-br](https://tfhub.dev/google/universal-sentence-encoder-cmlm/... |
sshleifer/student_marian_en_ro_6_1 | b674385d132cfc2dc92b51f7e2de78f3f2610db0 | 2020-08-26T23:33:54.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sshleifer | null | sshleifer/student_marian_en_ro_6_1 | 676 | null | transformers | 2,067 | Entry not found |
has-abi/bert-finetuned-resumes-sections | b9a6a9c36f3e6af01a45ab15b6f24b772954e288 | 2022-05-31T04:07:31.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | has-abi | null | has-abi/bert-finetuned-resumes-sections | 675 | 1 | transformers | 2,068 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-finetuned-resumes-sections
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 c... |
pysentimiento/robertuito-base-uncased | d8b419fbeb715ecf382cfcdd374bc8bb32f41ed8 | 2022-01-12T15:12:54.000Z | [
"pytorch",
"roberta",
"fill-mask",
"es",
"arxiv:2111.09453",
"transformers",
"twitter",
"masked-lm",
"autotrain_compatible"
] | fill-mask | false | pysentimiento | null | pysentimiento/robertuito-base-uncased | 674 | 5 | transformers | 2,069 | ---
language:
- es
tags:
- twitter
- masked-lm
---
# robertuito-base-uncased
# RoBERTuito
## A pre-trained language model for social media text in Spanish
[**PAPER**](https://arxiv.org/abs/2111.09453)
[Github Repository](https://github.com/pysentimiento/robertuito)
*RoBERTuito* is a pre-trained language ... |
seeksery/DialoGPT-calig3 | 1910866d1c3cf0c7b95c91ca1afd63285a825687 | 2022-07-28T03:16:28.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | seeksery | null | seeksery/DialoGPT-calig3 | 674 | null | transformers | 2,070 | ---
tags:
- conversational
--- |
Parth/result | b06ca90f3eda5e5ee4e1dc3a55714e7cb5ffcc00 | 2021-06-23T03:47:48.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Parth | null | Parth/result | 673 | 1 | transformers | 2,071 | Entry not found |
flax-community/gpt2-bengali | cb8fff6e5e2c459c057ce2d1a8e14fd79bb0f0a1 | 2021-09-25T08:06:37.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"bn",
"dataset:mc4",
"transformers",
"license:mit"
] | text-generation | false | flax-community | null | flax-community/gpt2-bengali | 673 | 2 | transformers | 2,072 | ---
language: bn
license: mit
datasets:
- mc4
---
# Bengali GPT-2
Bengali GPT-2 demo. Part of the [Huggingface JAX/Flax event](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/). Also features a [finetuned](https://huggingface.co/khalidsaifullaah/bengali-lyricist-gpt2?... |
nlpconnect/roberta-base-squad2-nq | e1c8537df9b745577d04e5353df510b000e2c6e8 | 2022-07-27T10:46:50.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"dataset:squad_v2",
"dataset:natural_questions",
"transformers",
"qa",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | nlpconnect | null | nlpconnect/roberta-base-squad2-nq | 673 | 2 | transformers | 2,073 | ---
tags:
- qa
license: apache-2.0
datasets:
- squad_v2
- natural_questions
model-index:
- name: nlpconnect/roberta-base-squad2-nq
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
... |
IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Sentiment | 054ef75752a9d18c8643d7adb49d2a050a70493f | 2022-05-16T06:07:55.000Z | [
"pytorch",
"megatron-bert",
"text-classification",
"zh",
"transformers",
"bert",
"NLU",
"Sentiment",
"license:apache-2.0"
] | text-classification | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Sentiment | 673 | null | transformers | 2,074 | ---
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- Sentiment
inference: true
widget:
- text: "今天心情不好"
---
# Erlangshen-MegatronBert-1.3B-Semtiment, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
We collect 8 sentiment datasets in the Chinese domain for fin... |
textattack/bert-base-uncased-QNLI | a63ef5bad18761ededbc04fb8e0f0a2729b1508d | 2021-05-20T07:33:46.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/bert-base-uncased-QNLI | 672 | null | transformers | 2,075 | Entry not found |
jy46604790/Fake-News-Bert-Detect | 8b42d870a3afb7f3bc683a7df73436137fce670a | 2022-04-26T04:36:13.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"license:apache-2.0"
] | text-classification | false | jy46604790 | null | jy46604790/Fake-News-Bert-Detect | 672 | 1 | transformers | 2,076 | ---
license: apache-2.0
---
# Fake News Recognition
## Overview
This model is trained by over 40,000 news from different medias based on the 'roberta-base'. It can give result by simply entering the text of the news less than 500 words(the excess will be truncated automatically).
LABEL_0: Fake news
LABEL_1: Real... |
Chalponkey/DialoGPT-small-Barry | d1bc56145314f22364461aa4d83f7b06b0f6e3b6 | 2021-09-11T22:36:06.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Chalponkey | null | Chalponkey/DialoGPT-small-Barry | 671 | null | transformers | 2,077 | ---
tags:
- conversational
---
#help why did i feed this bot the bee movie |
razent/SciFive-large-Pubmed_PMC | d6e6df3eda25df2b4cb1d869cdaac27c0616129e | 2022-03-20T17:46:44.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"dataset:pubmed",
"dataset:pmc/open_access",
"arxiv:2106.03598",
"transformers",
"token-classification",
"text-classification",
"question-answering",
"text-generation",
"autotrain_compatible"
] | text-classification | false | razent | null | razent/SciFive-large-Pubmed_PMC | 671 | 2 | transformers | 2,078 | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
- pmc/open_access
---
# SciFive Pubmed+PMC Large
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/a... |
Luyu/co-condenser-wiki | 2038532a382e4299d72fb9bc698dd4b2470d780f | 2021-08-13T13:50:11.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Luyu | null | Luyu/co-condenser-wiki | 669 | null | transformers | 2,079 | Entry not found |
poom-sci/WangchanBERTa-finetuned-sentiment | b78d07121acca2cbf53d0a81739cc0d03b033902 | 2021-11-05T17:48:02.000Z | [
"pytorch",
"tensorboard",
"camembert",
"text-classification",
"th",
"dataset:wongnai_reviews",
"dataset:wisesight_sentiment",
"dataset:generated_reviews_enth",
"transformers",
"sentiment-analysis",
"license:apache-2.0"
] | text-classification | false | poom-sci | null | poom-sci/WangchanBERTa-finetuned-sentiment | 669 | 1 | transformers | 2,080 | ---
language:
- th
tags:
- sentiment-analysis
license: apache-2.0
datasets:
- wongnai_reviews
- wisesight_sentiment
- generated_reviews_enth
widget:
- text: "โอโห้ ช่องนี้เปิดโลกเรามากเลยค่ะ คือตอนช่วงหาคำตอบเรานี่อึ้งไปเลย ดูจีเนียสมากๆๆ"
example_title: "Positive"
- text: "เริ่มจากชายเน็ตคนหนึ่งเปิดประเด็นว่าไปพบเจ้... |
arch0345/DialoGPT-small-joshua | 7c6d443dcabf0c95c723db2aa638e904e94eacc5 | 2021-06-03T23:29:44.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:mit"
] | conversational | false | arch0345 | null | arch0345/DialoGPT-small-joshua | 668 | null | transformers | 2,081 | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
tags:
- conversational
license: mit
---
Chat with the model:
```python
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("r3dhummingbird/DialoGPT-medium-joshua")
model = AutoModelWithLMHead.from_pr... |
fujiki/t5-efficient-xl-en2ja | f1591edfdaf0b9fc7d011fc073612d8f7b3967c5 | 2022-07-04T00:49:55.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | fujiki | null | fujiki/t5-efficient-xl-en2ja | 668 | null | transformers | 2,082 | ---
license: afl-3.0
---
|
google/multiberts-seed_1 | fc707bb7657051cf7d3ac47eecfbcad470de3206 | 2021-11-05T22:09:07.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_1",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_1 | 667 | null | transformers | 2,083 | ---
language: en
tags:
- multiberts
- multiberts-seed_1
license: apache-2.0
---
# MultiBERTs - Seed 1
MultiBERTs is a collection of checkpoints and a statistical library to support
robust research on BERT. We provide 25 BERT-base models trained with
similar hyper-parameters as
[the original BERT model](https://gi... |
DaNLP/da-bert-tone-sentiment-polarity | 2a4e7c0f815d586190c656fa5214969e01dd0639 | 2021-09-23T13:37:18.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"da",
"dataset:Twitter Sentiment",
"dataset:Europarl Sentiment",
"transformers",
"sentiment",
"polarity",
"license:cc-by-sa-4.0"
] | text-classification | false | DaNLP | null | DaNLP/da-bert-tone-sentiment-polarity | 666 | 2 | transformers | 2,084 | ---
language:
- da
tags:
- bert
- pytorch
- sentiment
- polarity
license: cc-by-sa-4.0
datasets:
- Twitter Sentiment
- Europarl Sentiment
metrics:
- f1
widget:
- text: Det er super godt
---
# Danish BERT Tone for sentiment polarity detection
The BERT Tone model detects sentiment polarity (positive, neutral or negativ... |
microsoft/beit-base-finetuned-ade-640-640 | 3b27791dc6f9f3278e47f226e98e2558422b8365 | 2022-02-22T09:06:59.000Z | [
"pytorch",
"beit",
"dataset:scene_parse_150",
"arxiv:2106.08254",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | microsoft | null | microsoft/beit-base-finetuned-ade-640-640 | 664 | 2 | transformers | 2,085 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- scene_parse_150
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_... |
aychang/bert-base-cased-trec-coarse | b3b6ddf0f7959ba9de759eeea77cce8b8d68556e | 2021-05-19T12:05:27.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"dataset:trec",
"transformers",
"license:mit"
] | text-classification | false | aychang | null | aychang/bert-base-cased-trec-coarse | 663 | null | transformers | 2,086 | ---
language:
- en
thumbnail:
tags:
- text-classification
license: mit
datasets:
- trec
metrics:
---
# bert-base-cased trained on TREC 6-class task
## Model description
A simple base BERT model trained on the "trec" dataset.
## Intended uses & limitations
#### How to use
##### Transformers
```python
# Load mod... |
jonatasgrosman/wav2vec2-large-xlsr-53-arabic | 3a200094b44306af86f8732637089706f0277293 | 2022-07-27T23:35:30.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"dataset:common_voice",
"dataset:arabic_speech_corpus",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-large-xlsr-53-arabic | 663 | null | transformers | 2,087 | ---
language: ar
datasets:
- common_voice
- arabic_speech_corpus
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Arabic by Jonatas Grosman
results:
- task:
name: Speech Recognition
type: automatic-... |
google/bert_uncased_L-2_H-768_A-12 | 18174647239b765f3d4aca187ac63f954d01d726 | 2021-05-19T17:29:34.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-2_H-768_A-12 | 662 | null | transformers | 2,088 | ---
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... |
sentence-transformers/bert-base-nli-max-tokens | c89b0d9813cc872c23740b2e08ea6210b3c059c5 | 2022-06-15T22:03:57.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/bert-base-nli-max-tokens | 659 | null | sentence-transformers | 2,089 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
license: apache-2.0
---
**⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net... |
AimB/mT5-en-kr-natural | 7a0a905bf442d55d6491d918ac2d94e8bd1ba6d8 | 2021-04-28T12:47:22.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | AimB | null | AimB/mT5-en-kr-natural | 658 | 1 | transformers | 2,090 | you can use this model with simpletransfomers.
```
!pip install simpletransformers
from simpletransformers.t5 import T5Model
model = T5Model("mt5", "AimB/mT5-en-kr-natural")
print(model.predict(["I feel good today"]))
print(model.predict(["우리집 고양이는 세상에서 제일 귀엽습니다"]))
``` |
nvidia/segformer-b2-finetuned-ade-512-512 | 39422f0171e069e930136843906418d07e563d4e | 2022-07-20T09:53:33.000Z | [
"pytorch",
"tf",
"segformer",
"dataset:scene_parse_150",
"arxiv:2105.15203",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | nvidia | null | nvidia/segformer-b2-finetuned-ade-512-512 | 654 | null | transformers | 2,091 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- scene_parse_150
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_... |
clarin-pl/roberta-polish-kgr10 | e301525291c9e9c4047142f61a457e5df2f8492a | 2021-05-20T15:22:13.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | clarin-pl | null | clarin-pl/roberta-polish-kgr10 | 653 | 1 | transformers | 2,092 | # Work in Progress Polish RoBERTa
The model has been trained for about 5% time of the target. We will publish new increments as they will be trained.
The model pre-trained on KGR10 corpora.
More about model at [CLARIN-dspace](https://huggingface.co/clarin/roberta-polish-v1)
## Usage
## Huggingface model hub
## ... |
TencentGameMate/chinese-wav2vec2-large | 6e3d224a0a7e42a0dc86a66e21a2c245dbb8dfed | 2022-06-24T02:11:54.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"transformers",
"license:mit"
] | null | false | TencentGameMate | null | TencentGameMate/chinese-wav2vec2-large | 653 | 2 | transformers | 2,093 | ---
license: mit
---
Pretrained on 10k hours WenetSpeech L subset. More details in [TencentGameMate/chinese_speech_pretrain](https://github.com/TencentGameMate/chinese_speech_pretrain)
This model does not have a tokenizer as it was pretrained on audio alone.
In order to use this model speech recognition, a tokenizer... |
deepmind/multimodal-perceiver | bbfaf820b7445c1435f93813b7e17037ebea9b85 | 2021-12-11T13:27:24.000Z | [
"pytorch",
"perceiver",
"dataset:kinetics-700-2020",
"arxiv:2010.10864",
"arxiv:2107.14795",
"transformers",
"license:apache-2.0"
] | null | false | deepmind | null | deepmind/multimodal-perceiver | 652 | 3 | transformers | 2,094 | ---
license: apache-2.0
tags:
datasets:
- kinetics-700-2020
---
# Perceiver IO for multimodal autoencoding
Perceiver IO model trained on [Kinetics-700-2020](https://arxiv.org/abs/2010.10864) for auto-encoding videos that consist of images, audio and a class label. It was introduced in the paper [Perceiver IO: A Gener... |
Annas/the-world-machine | 2e28ca9b851c49915cf2a91a89f87c7ef9fff0fa | 2021-11-23T23:26:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Annas | null | Annas/the-world-machine | 651 | 1 | transformers | 2,095 | AI that knows everything about Oneshot Created by Annas and Gwitr using OpenAI GPT2
|
inokufu/flaubert-base-uncased-xnli-sts-finetuned-education | e17f3c06113d6fed6f32b713b87182ebef9af58b | 2022-07-26T10:59:20.000Z | [
"pytorch",
"flaubert",
"feature-extraction",
"fr",
"dataset:xnli",
"dataset:stsb_multi_mt",
"arxiv:1810.04805",
"arxiv:1809.05053",
"sentence-transformers",
"sentence-similarity",
"transformers",
"Education",
"xnli",
"stsb_multi_mt"
] | sentence-similarity | false | inokufu | null | inokufu/flaubert-base-uncased-xnli-sts-finetuned-education | 651 | 0 | sentence-transformers | 2,096 | ---
pipeline_tag: sentence-similarity
language: fr
tags:
- sentence-similarity
- transformers
- Education
- fr
- flaubert
- sentence-transformers
- feature-extraction
- xnli
- stsb_multi_mt
datasets:
- xnli
- stsb_multi_mt
---
# inokufu/bertheo
A [sentence-transformers](https://www.SBERT.net) model fine-tuned on cour... |
Helsinki-NLP/opus-mt-war-en | fbaf745add3ecbdbb88881ad233881aed1776174 | 2020-08-21T14:42:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"war",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-war-en | 650 | null | transformers | 2,097 | ---
language:
- war
- en
tags:
- translation
license: apache-2.0
---
### war-eng
* source group: Waray (Philippines)
* target group: English
* OPUS readme: [war-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/war-eng/README.md)
* model: transformer-align
* source language(s): war
* t... |
mrm8488/t5-base-finetuned-sarcasm-twitter | e97df79f1a218ee827917b7bda41cd368ab53765 | 2021-09-14T11:44:45.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-sarcasm-twitter | 650 | 4 | transformers | 2,098 | ---
language: en
widget:
- text: "As everybody knows Trump is by far the best USA president... XD"
---
# T5-base fine-tuned for Sarcasm Detection 🙄
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) base fine-tuned on [ Twitter Sarcasm Dataset](https://github.com/EducationalTest... |
PlanTL-GOB-ES/gpt2-base-bne | 44d91934b5885add0cfc7c6f922a16b5b0f853b4 | 2022-04-06T14:41:14.000Z | [
"pytorch",
"gpt2",
"text-generation",
"es",
"dataset:bne",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"license:apache-2.0"
] | text-generation | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/gpt2-base-bne | 648 | 6 | transformers | 2,099 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
datasets:
- "bne"
metrics:
- "ppl"
---
# GPT2-base trained with data from National Library of Spain (BNE)
## Model Description
GPT2-base-bne is a transformer-based model for the Spanish language. It is based on the [GPT-... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.