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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
mrm8488/RuPERTa-base | 677ce6c9e527ad01d4d7c4cb6a3d88b6feca4009 | 2021-05-20T18:15:46.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"es",
"transformers",
"autotrain_compatible"
] | fill-mask | false | mrm8488 | null | mrm8488/RuPERTa-base | 380 | null | transformers | 2,600 | ---
language: es
thumbnail: https://i.imgur.com/DUlT077.jpg
widget:
- text: "España es un país muy <mask> en la UE"
---
# RuPERTa: the Spanish RoBERTa 🎃<img src="https://abs-0.twimg.com/emoji/v2/svg/1f1ea-1f1f8.svg" alt="spain flag" width="25"/>
RuPERTa-base (uncased) is a [RoBERTa model](https://github.com/pytorch/... |
alisawuffles/roberta-large-wanli | b435dba21967eb5aef9744b84c61b5b103123ee0 | 2022-06-07T21:02:23.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:2201.05955",
"transformers"
] | text-classification | false | alisawuffles | null | alisawuffles/roberta-large-wanli | 380 | 2 | transformers | 2,601 | ---
widget:
- text: "I almost forgot to eat lunch.</s></s>I didn't forget to eat lunch."
- text: "I almost forgot to eat lunch.</s></s>I forgot to eat lunch."
- text: "I ate lunch.</s></s>I almost forgot to eat lunch."
---
This is an off-the-shelf roberta-large model finetuned on WANLI, the Worker-AI Collaborative ... |
Deniskin/gpt3_medium | e338af13162e52e22f5a89a9986e5f7f3f66fbec | 2021-05-21T09:41:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Deniskin | null | Deniskin/gpt3_medium | 379 | null | transformers | 2,602 | Entry not found |
Stevo/DiagloGPT-medium-spamton | 3667391bd5125de5c048b3934bb5fb86d514cc7c | 2021-11-17T17:42:36.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Stevo | null | Stevo/DiagloGPT-medium-spamton | 379 | 1 | transformers | 2,603 | ---
tags:
- conversational
---
@ Deltarune Spamton DialoGPT Model |
anton-l/wav2vec2-base-lang-id | 1d4eda836bb7b7c53053393b65ddfbe1811e4d10 | 2021-10-01T12:36:49.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"dataset:common_language",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | anton-l | null | anton-l/wav2vec2-base-lang-id | 379 | 3 | transformers | 2,604 | ---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- common_language
metrics:
- accuracy
model-index:
- name: wav2vec2-base-lang-id
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably pr... |
bioformers/bioformer-cased-v1.0 | 18d58ede143f4a89cc7a512e55dad960e4d3ad9f | 2021-11-11T22:13:21.000Z | [
"pytorch",
"tf",
"bert",
"fill-mask",
"en",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | bioformers | null | bioformers/bioformer-cased-v1.0 | 379 | 3 | transformers | 2,605 | ---
language:
- en
license: apache-2.0
---
Bioformer is a lightweight BERT model for biomedical text mining. Bioformer uses a biomedical vocabulary and is pre-trained from scratch only on biomedical domain corpora. Our experiments show that Bioformer is 3x as fast as BERT-base, and achieves comparable or even better ... |
textattack/bert-base-uncased-STS-B | 8a1d8f1cc0523b7af746daf104ddd0c1ce5911c1 | 2021-05-20T07:38:28.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/bert-base-uncased-STS-B | 379 | null | transformers | 2,606 | Entry not found |
sijunhe/nezha-cn-base | bc68bfa5072f5c06055a2b59ba4858e9eea5183f | 2022-06-24T03:53:56.000Z | [
"pytorch",
"nezha",
"fill-mask",
"arxiv:1909.00204",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | fill-mask | false | sijunhe | null | sijunhe/nezha-cn-base | 379 | 2 | transformers | 2,607 | ---
license: afl-3.0
---
**Please use 'Bert' related tokenizer classes and 'Nezha' related model classes**
[NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204)
Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jian... |
cambridgeltl/mirror-bert-base-uncased-sentence-drophead | a61b9b9024f427b7a562209fac022e85986e9f00 | 2021-09-19T22:47:41.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:2104.08027",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/mirror-bert-base-uncased-sentence-drophead | 378 | null | transformers | 2,608 | ---
language: en
tags:
- sentence-embeddings
- sentence-similarity
### cambridgeltl/mirror-bert-base-uncased-sentence-drophead
An unsupervised sentence encoder proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2104.08027.pdf), using [drophead](https://aclanthology.org/2020.findings-emnlp.178.pdf) instead of dropo... |
cointegrated/rubert-base-cased-dp-paraphrase-detection | 2288d9e23758fc028af565680d451d21f7693390 | 2022-06-29T12:54:01.000Z | [
"pytorch",
"bert",
"text-classification",
"ru",
"dataset:merionum/ru_paraphraser",
"transformers",
"sentence-similarity"
] | text-classification | false | cointegrated | null | cointegrated/rubert-base-cased-dp-paraphrase-detection | 378 | null | transformers | 2,609 | ---
language: ["ru"]
tags:
- sentence-similarity
- text-classification
datasets:
- merionum/ru_paraphraser
---
This is a version of paraphrase detector by DeepPavlov ([details in the documentation](http://docs.deeppavlov.ai/en/master/features/overview.html#ranking-model-docs)) ported to the `Transformers` format.
Al... |
Sheerwin02/DialoGPT-small-isla | 0b6dff78f1bfbb1cc4d50c6d099420b57a4968da | 2022-02-28T06:03:10.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Sheerwin02 | null | Sheerwin02/DialoGPT-small-isla | 378 | null | transformers | 2,610 | ---
tags:
- conversational
---
#isla DialoGPT Model
|
scales-okn/docket-language-model | 1339be44c4185b118318131a7fbca1d65f12c4ac | 2022-06-04T15:09:27.000Z | [
"pytorch",
"tensorboard",
"deberta-v2",
"fill-mask",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | scales-okn | null | scales-okn/docket-language-model | 378 | null | transformers | 2,611 | ---
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-large-ddlm
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. -->
# deberta-v3-large-ddlm
This model... |
flair/upos-multi-fast | 4610445ba7d097da7e0ff23c3a782e9c474382c8 | 2021-03-02T22:22:55.000Z | [
"pytorch",
"en",
"de",
"fr",
"it",
"nl",
"pl",
"es",
"sv",
"da",
"no",
"fi",
"cs",
"dataset:ontonotes",
"flair",
"token-classification",
"sequence-tagger-model"
] | token-classification | false | flair | null | flair/upos-multi-fast | 377 | 4 | flair | 2,612 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
language:
- en
- de
- fr
- it
- nl
- pl
- es
- sv
- da
- no
- fi
- cs
datasets:
- ontonotes
widget:
- text: "Ich liebe Berlin, as they say."
---
## Multilingual Universal Part-of-Speech Tagging in Flair (fast model)
This is the fast multilingual uni... |
uclanlp/visualbert-nlvr2-coco-pre | 155352ba56549d808a84e5c1f891300bf24f019b | 2021-05-31T11:11:50.000Z | [
"pytorch",
"visual_bert",
"pretraining",
"transformers"
] | null | false | uclanlp | null | uclanlp/visualbert-nlvr2-coco-pre | 377 | null | transformers | 2,613 | Entry not found |
kakife3586/bad | 19f022d577b7ff8b69f87a3c89aa066405398985 | 2022-07-22T19:16:26.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | kakife3586 | null | kakife3586/bad | 377 | 1 | transformers | 2,614 | Entry not found |
KoboldAI/GPT-Neo-1.3B-Adventure | 803261b84356c383860f1140667bc49c7cfff2dc | 2022-03-22T09:49:48.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"en",
"transformers",
"license:mit"
] | text-generation | false | KoboldAI | null | KoboldAI/GPT-Neo-1.3B-Adventure | 376 | 1 | transformers | 2,615 | ---
language: en
license: mit
pipeline_tag: text-generation
---
# GPT-Neo 1.3B - Adventure
## Model Description
GPT-Neo 1.3B-Adventure is a finetune created using EleutherAI's GPT-Neo 1.3B model.
## Training data
The training data is a direct copy of the "cys" dataset by VE, a CYOA-based dataset.
### How to u... |
Adapting/dialogue_agent_nlplab2022 | 51060a1364717812d951374c778573eae185f053 | 2022-06-30T07:46:33.000Z | [
"pytorch",
"blenderbot",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Adapting | null | Adapting/dialogue_agent_nlplab2022 | 376 | null | transformers | 2,616 | Dataset trained on: https://huggingface.co/datasets/Adapting/empathetic_dialogues_with_special_tokens
Commit hash of model versions
1. blenderbot-400M-distill - 10 epochs fine-tuning: **b86f62986872b4c1a9921acdb8cd226761d736cf**
2. blenderbot-400M-distill - 20 epochs fine-tuning: **e803a10542ea7e4f116e89aca0f7250fb71a... |
cahya/distilbert-base-indonesian | 9e948656420019310c5334dfcc3dd086c67d405a | 2021-02-08T09:06:09.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"id",
"dataset:wikipedia",
"dataset:id_newspapers_2018",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | cahya | null | cahya/distilbert-base-indonesian | 375 | 1 | transformers | 2,617 | ---
language: "id"
license: "mit"
datasets:
- wikipedia
- id_newspapers_2018
widget:
- text: "ayahku sedang bekerja di sawah untuk [MASK] padi."
---
# Indonesian DistilBERT base model (uncased)
## Model description
This model is a distilled version of the [Indonesian BERT base model](https://huggingface.co/cahya/ber... |
clagator/biobert_squad2_cased | e7545839557ddb772e1d4df26c5fd26de41592a2 | 2021-05-19T14:22:23.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | clagator | null | clagator/biobert_squad2_cased | 375 | null | transformers | 2,618 | Entry not found |
smmzhu/DialoGPT-medium-sam | 3c41a977ed304546e1185275414a4ab2225562a1 | 2022-07-11T06:58:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | smmzhu | null | smmzhu/DialoGPT-medium-sam | 375 | null | transformers | 2,619 | ---
tags:
- conversational
---
# My Awesome Model |
Doquey/DialoGPT-small-Luisbot1 | 6da56bf264c4fb5f49e835aed78342293bc7da40 | 2021-09-01T23:20:51.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Doquey | null | Doquey/DialoGPT-small-Luisbot1 | 373 | null | transformers | 2,620 | ---
tags:
- conversational
---
#Rick DialoGPT model |
Geotrend/bert-base-en-zh-cased | eebc9a2d0689a2073d0b0dd401e5d0decfa2864c | 2021-05-18T19:52:44.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"multilingual",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-en-zh-cased | 373 | null | transformers | 2,621 | ---
language: multilingual
datasets: wikipedia
license: apache-2.0
widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---
# bert-base-en-zh-cased
We are sharing smaller versions of [bert-base-multilingual-cased... |
valurank/distilroberta-clickbait | 294a3fc0c737db43110a157136edb0e7728c28ac | 2022-06-08T20:24:26.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/distilroberta-clickbait | 373 | null | transformers | 2,622 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-clickbait
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilroberta-cl... |
Xuhui/ToxDect-roberta-large | 7b97c89938cb241d3ae9235257bbe4916d4f0c75 | 2021-11-07T16:35:03.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:2102.00086",
"transformers"
] | text-classification | false | Xuhui | null | Xuhui/ToxDect-roberta-large | 372 | 2 | transformers | 2,623 | ---
language:
-
-
thumbnail:
tags:
-
-
-
license:
datasets:
-
-
metrics:
-
-
---
# Toxic language detection
## Model description
A toxic language detection model trained on tweets. The base model is Roberta-large. For more information,
including the **training data**, **limitations and bias**, please refer ... |
asahi417/tner-xlm-roberta-base-uncased-ontonotes5 | 580551e1a8cf979711f3956848e4479345bd045f | 2021-02-13T00:08:01.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | asahi417 | null | asahi417/tner-xlm-roberta-base-uncased-ontonotes5 | 372 | 1 | transformers | 2,624 | # XLM-RoBERTa for NER
XLM-RoBERTa finetuned on NER. Check more detail at [TNER repository](https://github.com/asahi417/tner).
## Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-xlm-roberta-base-uncased-ontonotes5")
m... |
cahya/bert-base-indonesian-1.5G | a4400ab68607dea3f7f1522f9fed74909980bd77 | 2021-05-19T13:37:31.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"id",
"dataset:wikipedia",
"dataset:id_newspapers_2018",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | cahya | null | cahya/bert-base-indonesian-1.5G | 372 | 0 | transformers | 2,625 | ---
language: "id"
license: "mit"
datasets:
- wikipedia
- id_newspapers_2018
widget:
- text: "Ibu ku sedang bekerja [MASK] sawah."
---
# Indonesian BERT base model (uncased)
## Model description
It is BERT-base model pre-trained with indonesian Wikipedia and indonesian newspapers using a masked language modeling (ML... |
Maxwere/DiabloGPT-medium-maxbot | 618d143972c3cfb64458586ab6a26fa62de8e5e3 | 2022-03-03T00:41:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Maxwere | null | Maxwere/DiabloGPT-medium-maxbot | 372 | null | transformers | 2,626 | ---
tags:
- conversational
---
# Max DiabloGPT Model |
Artem1/t5_squad_v1 | 8a6a2db32c91a1c1fa48c05b1740b22cb9fcdbd6 | 2022-07-12T11:25:18.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Artem1 | null | Artem1/t5_squad_v1 | 372 | null | transformers | 2,627 | Entry not found |
ChrisVCB/DialoGPT-medium-cmjs | 705a3520a4cb682316d11b238d89be3135da4f34 | 2021-12-10T20:02:45.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ChrisVCB | null | ChrisVCB/DialoGPT-medium-cmjs | 371 | null | transformers | 2,628 | ---
tags:
- conversational
---
# CMJS DialoGPT Model |
SajjadAyoubi/bert-base-fa-qa | 610d047db3fcef30d0811d44bef629c69beba299 | 2021-05-18T22:30:21.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | SajjadAyoubi | null | SajjadAyoubi/bert-base-fa-qa | 371 | 5 | transformers | 2,629 | ### How to use
#### Requirements
Transformers require `transformers` and `sentencepiece`, both of which can be
installed using `pip`.
```sh
pip install transformers sentencepiece
```
#### Pipelines 🚀
In case you are not familiar with Transformers, you can use pipelines instead.
Note that, pipelines can't have _no... |
castorini/ance-msmarco-doc-firstp | 5b60aa5a8612e3db04390a0e91fda0d3154b0a8e | 2021-05-20T15:17:20.000Z | [
"pytorch",
"roberta",
"arxiv:2007.00808",
"transformers"
] | null | false | castorini | null | castorini/ance-msmarco-doc-firstp | 371 | null | transformers | 2,630 | This model is converted from the original ANCE [repo](https://github.com/microsoft/ANCE) and fitted into Pyserini:
> Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, Arnold Overwijk. [Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval](https://arx... |
elgeish/cs224n-squad2.0-albert-base-v2 | 95a8cdd3beb799d79384b8b50f310edefeb97492 | 2020-12-11T21:38:54.000Z | [
"pytorch",
"albert",
"question-answering",
"arxiv:2004.07067",
"transformers",
"exbert",
"autotrain_compatible"
] | question-answering | false | elgeish | null | elgeish/cs224n-squad2.0-albert-base-v2 | 371 | null | transformers | 2,631 | ---
tags:
- exbert
---
## CS224n SQuAD2.0 Project Dataset
The goal of this model is to save CS224n students GPU time when establishing
baselines to beat for the [Default Final Project](http://web.stanford.edu/class/cs224n/project/default-final-project-handout.pdf).
The training set used to fine-tune this model is the ... |
sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base | 3320b11eacb143b6e6e6d71b727224dbd8f8b65a | 2021-08-05T08:22:43.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base | 371 | null | sentence-transformers | 2,632 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base
This is a port of the [DPR Model](https://github.com/facebookresearch/DPR) to [sentence-transformers](ht... |
ShreyaR/finetuned-roberta-depression | a34232531498f0975e3c67ce0ce02ebd9488945c | 2022-05-20T04:38:42.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | ShreyaR | null | ShreyaR/finetuned-roberta-depression | 371 | 5 | transformers | 2,633 | ---
license: mit
tags:
- generated_from_trainer
widget:
- text: "I feel so low and numb, don't feel like doing anything. Just passing my days"
- text: "Sleep is my greatest and most comforting escape whenever I wake up these days. The literal very first emotion I feel is just misery and reminding myself of all my probl... |
dbmdz/bert-base-cased-finetuned-conll03-english | 4a108fba55732fd6570a15f7475ba13e83c6b8c5 | 2021-05-19T14:43:37.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | dbmdz | null | dbmdz/bert-base-cased-finetuned-conll03-english | 369 | null | transformers | 2,634 | Entry not found |
Starry/KARENTRIES | a256558b696d33b1aa2ed352ed15aad2b0c53116 | 2022-03-10T17:59:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Starry | null | Starry/KARENTRIES | 369 | null | transformers | 2,635 | ---
tags:
- conversational
---
# DialoGPT model |
KoboldAI/OPT-6B-nerys-v2 | 9e1f1498391df2c28ce35a9290a5a24b8022a43b | 2022-07-04T07:45:47.000Z | [
"pytorch",
"opt",
"text-generation",
"en",
"arxiv:2205.01068",
"transformers",
"license:other"
] | text-generation | false | KoboldAI | null | KoboldAI/OPT-6B-nerys-v2 | 369 | 2 | transformers | 2,636 | ---
language: en
license: other
commercial: no
---
# OPT 6B - Nerys
## Model Description
OPT 6B-Nerys is a finetune created using Facebook's OPT model.
## Training data
The training data contains around 2500 ebooks in various genres (the "Pike" dataset), a CYOA dataset called "CYS" and 50 Asian "Light Novels" (the "Man... |
csebuetnlp/mT5_m2o_russian_crossSum | 6eedefa5d23a200078f75cb69430fa663562ff36 | 2022-04-22T15:05:47.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"am",
"ar",
"az",
"bn",
"my",
"zh",
"en",
"fr",
"gu",
"ha",
"hi",
"ig",
"id",
"ja",
"rn",
"ko",
"ky",
"mr",
"ne",
"om",
"ps",
"fa",
"pcm",
"pt",
"pa",
"ru",
"gd",
"sr",
"si",
"so",
"es",
"sw",
"ta",
"te... | summarization | false | csebuetnlp | null | csebuetnlp/mT5_m2o_russian_crossSum | 368 | null | transformers | 2,637 | ---
tags:
- summarization
- mT5
language:
- am
- ar
- az
- bn
- my
- zh
- en
- fr
- gu
- ha
- hi
- ig
- id
- ja
- rn
- ko
- ky
- mr
- ne
- om
- ps
- fa
- pcm
- pt
- pa
- ru
- gd
- sr
- si
- so
- es
- sw
- ta
- te
- th
- ti
- tr
- uk
- ur
- uz
- vi
- cy
- yo
licenses:
- cc-by-nc-sa-4.0
widget:
- text: "Videos that say a... |
google/ddpm-celebahq-256 | cd5c944777ea2668051904ead6cc120739b86c4d | 2022-07-21T15:00:31.000Z | [
"diffusers",
"arxiv:2006.11239",
"pytorch",
"unconditional-image-generation",
"license:apache-2.0"
] | unconditional-image-generation | false | google | null | google/ddpm-celebahq-256 | 368 | 2 | diffusers | 2,638 | ---
license: apache-2.0
tags:
- pytorch
- diffusers
- unconditional-image-generation
---
# Denoising Diffusion Probabilistic Models (DDPM)
**Paper**: [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239)
**Authors**: Jonathan Ho, Ajay Jain, Pieter Abbeel
**Abstract**:
*We present high qualit... |
Lauler/deformer | 8c196932a1fee0f57293b4a9ad0e0e49fc469145 | 2021-12-29T07:21:08.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Lauler | null | Lauler/deformer | 367 | null | transformers | 2,639 | ---
widget:
- text: "dem har sökt upp de för att prata."
example_title: "de/dem exempel 1"
- text: "Jag såg de komma runt hörnet och gå i riktning mot dem byggnaderna."
example_title: "de/dem exempel 2"
---
## DeFormer
DeFormer är en modell som har tränats på att skilja mellan `de` och `dem` i svenska meningar. M... |
Muennighoff/SGPT-5.8B-weightedmean-msmarco-specb-bitfit | 62a5cc04518c1339a2c88bdaa63f1dedaa61146a | 2022-06-19T06:34:12.000Z | [
"pytorch",
"gptj",
"feature-extraction",
"arxiv:2202.08904",
"sentence-transformers",
"sentence-similarity"
] | sentence-similarity | false | Muennighoff | null | Muennighoff/SGPT-5.8B-weightedmean-msmarco-specb-bitfit | 367 | 2 | sentence-transformers | 2,640 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# SGPT-5.8B-weightedmean-msmarco-specb-bitfit
## Usage
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt
## Evaluation Results
For eval results, refer to our paper: h... |
kornosk/bert-election2020-twitter-stance-biden-KE-MLM | b8913cc4d8d2e857667f20908c0c028bd3d1183d | 2022-05-02T22:58:37.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"transformers",
"twitter",
"stance-detection",
"election2020",
"politics",
"license:gpl-3.0"
] | text-classification | false | kornosk | null | kornosk/bert-election2020-twitter-stance-biden-KE-MLM | 367 | 1 | transformers | 2,641 | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Joe Biden (KE-MLM)
Pre-trained weights for **KE-MLM model** in [Knowledge Enhance Masked Language Model for Stance Detection](https://www.a... |
roberta-base-openai-detector | 2de46c869ee117c00af7b2e9e4cba743c2cbc778 | 2022-07-22T08:00:35.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1904.09751",
"arxiv:1910.09700",
"transformers",
"exbert",
"license:mit"
] | text-classification | false | null | null | roberta-base-openai-detector | 366 | 3 | transformers | 2,642 | ---
language: en
license: mit
tags:
- exbert
datasets:
- bookcorpus
- wikipedia
---
# RoBERTa Base OpenAI Detector
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Environment... |
ivanlau/language-detection-fine-tuned-on-xlm-roberta-base | 4207aaa00b26aea91d99cb1abc2d7f56814fbe05 | 2021-12-17T10:33:13.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"text-classification",
"dataset:common_language",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | ivanlau | null | ivanlau/language-detection-fine-tuned-on-xlm-roberta-base | 366 | 1 | transformers | 2,643 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- common_language
metrics:
- accuracy
model-index:
- name: language-detection-fine-tuned-on-xlm-roberta-base
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: common_language
type: common_language... |
valurank/finetuned-distilbert-news-article-categorization | 3046ba5378260ac2ed8b7c49265fd1f4e9e68d97 | 2022-07-03T21:23:38.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/finetuned-distilbert-news-article-categorization | 366 | null | transformers | 2,644 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: finetuned-distilbert-news-article-categorization
results: []
---
### finetuned-distilbert-news-article-catgorization
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the news_arti... |
SI2M-Lab/DarijaBERT | f88ae61231ac5b42ced6733310b92a2133ea67a7 | 2022-06-20T14:55:01.000Z | [
"pytorch",
"bert",
"fill-mask",
"ar",
"transformers",
"autotrain_compatible"
] | fill-mask | false | SI2M-Lab | null | SI2M-Lab/DarijaBERT | 365 | 3 | transformers | 2,645 | ---
language: ar
widget:
- text: " جاب ليا [MASK] ."
- text: "مشيت نجيب[MASK] فالفرماسيان ."
---
AIOX Lab and SI2M Lab INSEA have joined forces to offer researchers, industrialists and the NLP (Natural Language Processing) community the first intelligent Open Source system that understands Moroccan dialectal langu... |
NlpHUST/t5-small-vi-summarization | d579ec553e3bd8574413a7736a005acea50f8508 | 2021-06-23T03:36:33.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | NlpHUST | null | NlpHUST/t5-small-vi-summarization | 365 | 1 | transformers | 2,646 | # T5-SMALL-SUMMARIZATION :Pretraining Text-To-Text Transfer Transformer for Vietnamese Text Summarization
#### Example Using
``` bash
import torch
from transformers import T5ForConditionalGeneration, T5Tokenizer
import torch
if torch.cuda.is_available():
device = torch.device("cuda")
print('There are... |
ajitrajasekharan/biomedical | dfd137b5429ef4e3ca250053967f4384b6a99c02 | 2022-02-05T08:44:05.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | ajitrajasekharan | null | ajitrajasekharan/biomedical | 364 | 1 | transformers | 2,647 | ---
language:
- {en} # Example: fr
license: mit
widget:
- text: "Lou Gehrig who works for XCorp and lives in New York suffers from [MASK]"
example_title: "Test for entity type: Disease"
- text: "Overexpression of [MASK] occurs across a wide range of cancers"
example_title: "Test for entity type: Gene"
- text: "Pat... |
minimaxir/reddit | d8caacc8da7948b068192e398f0d9b4d5137d815 | 2021-05-23T09:36:11.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | minimaxir | null | minimaxir/reddit | 364 | 0 | transformers | 2,648 | Entry not found |
TurkuNLP/wikibert-base-en-cased | aba47c7a4b7f05ea5ec5e645e0843d31d9018f18 | 2020-05-24T19:59:24.000Z | [
"pytorch",
"transformers"
] | null | false | TurkuNLP | null | TurkuNLP/wikibert-base-en-cased | 363 | null | transformers | 2,649 | Entry not found |
facebook/wav2vec2-xls-r-1b-21-to-en | 286d0470e6ed5468b5a4ef0a9bd15b0aebe1a034 | 2022-05-26T22:24:32.000Z | [
"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-1b-21-to-en | 363 | 1 | transformers | 2,650 | ---
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
l... |
google/realm-cc-news-pretrained-embedder | ba2b2d766d08235b15608e0b95f2bbbe3f8dfed6 | 2022-01-05T18:47:59.000Z | [
"pytorch",
"realm",
"en",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/realm-cc-news-pretrained-embedder | 363 | null | transformers | 2,651 | ---
language: en
license: apache-2.0
---
# realm-cc-news-pretrained-embedder
## Model description
The REALM checkpoint pretrained with CC-News as target corpus and Wikipedia as knowledge corpus, converted from the TF checkpoint provided by Google Language.
The original paper, code, and checkpoints can be found [her... |
anton-l/wav2vec2-base-superb-sd | 3b9021739e0bb551b176f8acb7e5a8a0cf33d944 | 2021-12-14T09:57:00.000Z | [
"pytorch",
"wav2vec2",
"audio-frame-classification",
"transformers"
] | null | false | anton-l | null | anton-l/wav2vec2-base-superb-sd | 362 | null | transformers | 2,652 | |
google/tapas-small-finetuned-sqa | 7b8f70a63c913442114f3b6b516d48657f044f0a | 2021-11-29T13:09:34.000Z | [
"pytorch",
"tf",
"tapas",
"table-question-answering",
"en",
"dataset:msr_sqa",
"arxiv:2004.02349",
"arxiv:2010.00571",
"transformers",
"license:apache-2.0"
] | table-question-answering | false | google | null | google/tapas-small-finetuned-sqa | 362 | null | transformers | 2,653 | ---
language: en
tags:
- tapas
license: apache-2.0
datasets:
- msr_sqa
---
# TAPAS small model fine-tuned on Sequential Question Answering (SQA)
This model has 2 versions which can be used. The default version corresponds to the `tapas_sqa_inter_masklm_small_reset` checkpoint of the [original Github repository](https... |
microsoft/beit-large-patch16-512 | f03bc4a94ad012c74bdd32d80ec7169a751034f9 | 2022-01-28T10:20:07.000Z | [
"pytorch",
"jax",
"beit",
"image-classification",
"dataset:imagenet",
"dataset:imagenet-21k",
"arxiv:2106.08254",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/beit-large-patch16-512 | 362 | 1 | transformers | 2,654 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-21k
---
# BEiT (large-sized model, fine-tuned on ImageNet-1k)
BEiT model pre-trained in a self-supervised fashion on ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1... |
BrunoNogueira/DialoGPT-kungfupanda | 89c1a1f2bb2c5ab517ec9319094a8c0405de9240 | 2021-09-23T18:49:17.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | BrunoNogueira | null | BrunoNogueira/DialoGPT-kungfupanda | 361 | null | transformers | 2,655 | ---
tags:
- conversational
---
#DialoGPT-kungfupanda |
aluserhuggingface/DialoGPT-small-harrypotter | 99262a7670e2d0053c5c46724110f4135fc33e67 | 2022-02-18T19:41:48.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | aluserhuggingface | null | aluserhuggingface/DialoGPT-small-harrypotter | 361 | null | transformers | 2,656 | ---
tags:
- conversational
---
#Harry Potter DialoGPT Model |
lassl/gpt2-ko-small | e7d6eaeacf4937a07a1c57394b9d70448b0a0141 | 2022-02-20T00:13:44.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ko",
"transformers",
"korean",
"lassl",
"license:apache-2.0"
] | text-generation | false | lassl | null | lassl/gpt2-ko-small | 361 | 3 | transformers | 2,657 | ---
license: apache-2.0
language: ko
tags:
- korean
- lassl
---
# LASSL gpt2-ko-small
## How to use
```python
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("lassl/gpt2-ko-small")
tokenizer = AutoTokenizer.from_pretrained("lassl/gpt2-ko-small")
```
## Evaluation
Evaulation r... |
poom-sci/bert-base-uncased-multi-emotion | 09b04517929ddbb0a90d439018418d47377bcac3 | 2021-11-14T16:22:26.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"en",
"dataset:go_emotions",
"transformers",
"translation",
"license:apache-2.0"
] | text-classification | false | poom-sci | null | poom-sci/bert-base-uncased-multi-emotion | 361 | null | transformers | 2,658 | ---
language:
- en
tags:
- translation
license: apache-2.0
datasets:
- go_emotions
---
created for study |
Narrativa/mT5-base-finetuned-tydiQA-question-generation | 5e36ab2e87781ca9cbd4e7101e6904c7e5cf7568 | 2021-08-23T10:05:14.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"multilingual",
"dataset:tydiqa",
"arxiv:2010.11934",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Narrativa | null | Narrativa/mT5-base-finetuned-tydiQA-question-generation | 360 | 1 | transformers | 2,659 | ---
language: multilingual
datasets:
- tydiqa
widget:
- text: "answer: monitoring and managing PR strategy including relations with the media and journalists context: Sofía has a degree in Communications and public relations agency experience where she was in charge of monitoring and managing PR strategy including rela... |
cpierse/gpt2_film_scripts | 423a12f965f84b34e8e9bd85cfb32e7cec634e7d | 2021-05-21T15:09:47.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | cpierse | null | cpierse/gpt2_film_scripts | 360 | null | transformers | 2,660 | Entry not found |
google/multiberts-seed_10 | 2eb55a013190f8ec91466b5cd9404699b379f48a | 2021-11-05T22:26:09.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_10",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_10 | 360 | null | transformers | 2,661 | ---
language: en
tags:
- multiberts
- multiberts-seed_10
license: apache-2.0
---
# MultiBERTs - Seed 10
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://... |
google/muril-large-cased | ace319f0d17524297957e249aff028b0b7357ab5 | 2021-10-16T03:28:16.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:1810.04805",
"arxiv:1911.02116",
"arxiv:2003.11080",
"arxiv:2009.05166",
"arxiv:2103.10730",
"transformers"
] | feature-extraction | false | google | null | google/muril-large-cased | 360 | 10 | transformers | 2,662 | # MuRIL Large
Multilingual Representations for Indian Languages : A BERT Large (24L) model pre-trained on 17 Indian languages, and their transliterated counterparts.
## Overview
This model uses a BERT large architecture [1] pretrained from scratch using the
Wikipedia [2], Common Crawl [3], PMINDIA [4] and Dakshina [5... |
google/realm-orqa-nq-openqa | ea416e495785cd9612f659b69af3a7857c91fe2a | 2022-01-05T18:00:40.000Z | [
"pytorch",
"realm",
"en",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/realm-orqa-nq-openqa | 360 | 2 | transformers | 2,663 | ---
language: en
license: apache-2.0
---
# realm-orqa-nq-openqa
## Model description
The REALM checkpoint finetuned with Natural Questions(NQ) dataset, converted from the TF checkpoint provided by Google Language.
The original paper, code, and checkpoints can be found [here](https://github.com/google-res... |
voidful/bart-distractor-generation | 31759a44a1319ed9804ba667cbb9b0cc03faff11 | 2021-04-04T16:18:19.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:race",
"transformers",
"distractor",
"generation",
"seq2seq",
"autotrain_compatible"
] | text2text-generation | false | voidful | null | voidful/bart-distractor-generation | 360 | 2 | transformers | 2,664 | ---
language: en
tags:
- bart
- distractor
- generation
- seq2seq
datasets:
- race
metrics:
- bleu
- rouge
pipeline_tag: text2text-generation
widget:
- text: "When you ' re having a holiday , one of the main questions to ask is which hotel or apartment to choose . However , when it comes to France , you have another sp... |
stanleychu2/system_400M | 954462cbb137d6b684df0a6daa60f135a528799b | 2022-03-07T09:10:43.000Z | [
"pytorch",
"blenderbot",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | stanleychu2 | null | stanleychu2/system_400M | 360 | null | transformers | 2,665 | Entry not found |
Batsy24/DialoGPT-medium-Twilight_BellaBot | da351b3d0906189e60536326b516606cce4210c6 | 2021-11-18T09:15:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Batsy24 | null | Batsy24/DialoGPT-medium-Twilight_BellaBot | 359 | null | transformers | 2,666 | ---
tags:
- conversational
---
# Bella Swan DialoGPT model |
ccdv/lsg-base-4096 | 63ab0e0d4b0b6d2c8d882070c6fa01d360c9b17b | 2022-07-25T05:36:08.000Z | [
"pytorch",
"roberta",
"fill-mask",
"en",
"transformers",
"long context",
"autotrain_compatible"
] | fill-mask | false | ccdv | null | ccdv/lsg-base-4096 | 359 | 1 | transformers | 2,667 | ---
language: en
tags:
- long context
---
# LSG model
**Transformers >= 4.18.0**\
**This model relies on a custom modeling file, you need to add trust_remote_code=True**\
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)**
* [Usage](#usage)
* [Parameters](#parameters)
* [Sparse selection type](... |
google/multiberts-seed_11 | d6aff2e50dfed3e7de6efc38459cb0070901f176 | 2021-11-05T22:28:19.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_11",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_11 | 359 | null | transformers | 2,668 | ---
language: en
tags:
- multiberts
- multiberts-seed_11
license: apache-2.0
---
# MultiBERTs - Seed 11
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://... |
google/multiberts-seed_12 | b6933aed309729c8305d033bbb9dde829a901c04 | 2021-11-05T22:30:05.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_12",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_12 | 359 | null | transformers | 2,669 | ---
language: en
tags:
- multiberts
- multiberts-seed_12
license: apache-2.0
---
# MultiBERTs - Seed 12
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://... |
google/multiberts-seed_8 | 95242f2431926edbd81cac9a7c643ce60193d979 | 2021-11-05T22:21:22.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_8",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_8 | 359 | null | transformers | 2,670 | ---
language: en
tags:
- multiberts
- multiberts-seed_8
license: apache-2.0
---
# MultiBERTs - Seed 8
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... |
google/multiberts-seed_9 | 225772f575cc16e5e1f27e06a6c4d888dc82ddab | 2021-11-05T22:23:00.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_9",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_9 | 359 | null | transformers | 2,671 | ---
language: en
tags:
- multiberts
- multiberts-seed_9
license: apache-2.0
---
# MultiBERTs - Seed 9
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... |
huggingface-course/distilbert-base-uncased-finetuned-imdb | 10abb8b26c1b5163624c5ccc649986aa7ace845b | 2021-11-11T17:42:21.000Z | [
"pytorch",
"tf",
"tensorboard",
"distilbert",
"fill-mask",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | huggingface-course | null | huggingface-course/distilbert-base-uncased-finetuned-imdb | 359 | null | transformers | 2,672 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: distilbert-base-uncased-finetuned-imdb
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 ... |
stanleychu2/user_400M | 96801813e5be15b4bc5b85529097e35019f973b5 | 2022-03-07T09:10:11.000Z | [
"pytorch",
"blenderbot",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | stanleychu2 | null | stanleychu2/user_400M | 359 | null | transformers | 2,673 | Entry not found |
jinmang2/kpfbert | e060b6039623d70d4b6df98245376f75a6e3a4e5 | 2022-04-05T16:03:00.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | jinmang2 | null | jinmang2/kpfbert | 359 | null | transformers | 2,674 | # KpfBERT
https://github.com/jinmang2/kpfbert |
tscholak/t5.1.1.lm100k.large | 9b42e0fff7709a21b3da746bf3fce8774d5136a2 | 2021-10-09T13:42:53.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | tscholak | null | tscholak/t5.1.1.lm100k.large | 358 | 1 | transformers | 2,675 | Entry not found |
l3cube-pune/hing-bert | fccd12879be703ba59ae4d306f4fb10685559812 | 2022-06-26T15:13:10.000Z | [
"pytorch",
"bert",
"fill-mask",
"hi",
"en",
"dataset:L3Cube-HingCorpus",
"arxiv:2204.08398",
"transformers",
"codemix",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | l3cube-pune | null | l3cube-pune/hing-bert | 358 | 1 | transformers | 2,676 | ---
license: cc-by-4.0
language:
- hi
- en
tags:
- hi
- en
- codemix
datasets:
- L3Cube-HingCorpus
---
## HingBERT
HingBERT is a Hindi-English code-mixed BERT model trained on roman text. It is a base BERT model fine-tuned on L3Cube-HingCorpus.
<br>
[dataset link] (https://github.com/l3cube-pune/code-mixed-nlp)
More... |
valurank/distilroberta-current | ed30e164cbf3eb30df98cb71576bad2098df9529 | 2022-06-08T20:20:10.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-classification | false | valurank | null | valurank/distilroberta-current | 358 | null | transformers | 2,677 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: distilroberta-current
results: []
---
# distilroberta-current
This model classifies articles as current (covering or discussing current events) or not current (not relating to current events).
The model is a fine-tuned version of [distilroberta... |
HYPJUDY/layoutlmv3-base-finetuned-funsd | 90be3a172349c0290245ffa81d41c6f5c9f24040 | 2022-07-19T02:25:28.000Z | [
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"arxiv:2204.08387",
"transformers",
"license:mit",
"autotrain_compatible"
] | token-classification | false | HYPJUDY | null | HYPJUDY/layoutlmv3-base-finetuned-funsd | 358 | 3 | transformers | 2,678 | ---
license: mit
---
# layoutlmv3-base-finetuned-funsd
The model [layoutlmv3-base-finetuned-funsd](https://huggingface.co/HYPJUDY/layoutlmv3-base-finetuned-funsd) is fine-tuned on the FUNSD dataset initialized from [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base).
This finetuned model achi... |
Wi/arxiv-topics-distilbert-base-cased | 20469cc8a5611f69a6b8911188d7dee8b27a493d | 2022-07-12T01:02:14.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"arxiv",
"topic-classification",
"license:apache-2.0"
] | text-classification | false | Wi | null | Wi/arxiv-topics-distilbert-base-cased | 358 | 0 | transformers | 2,679 | ---
language: en
license: apache-2.0
tags:
- arxiv
- topic-classification
- distilbert
widget:
- text: "Title: The Design of Radio Telescope Array Configurations using Multiobjective\n\
\ Optimization: Imaging Performance versus Cable Length\nAbstract: The next generation\
\ of radio telescope interferometric ... |
mymusise/CPM-Generate-distill | 1611f575f3db84c83fd120ca8fd826953b4afdbf | 2021-05-23T10:40:31.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"zh",
"transformers"
] | text-generation | false | mymusise | null | mymusise/CPM-Generate-distill | 357 | 4 | transformers | 2,680 | ---
language: zh
widget:
- text: "天下熙熙，"
- text: "天气不错，"
---
<h1 align="center">
CPM-Generate-distill
</h1>
CPM(Chinese Pre-Trained Language Models), which has 2.6B parameters, made by the research team of Beijing Zhiyuan Institute of artificial intelligence and Tsinghua University @TsinghuaAI.
[repo: CPM-Generate](... |
junnyu/wobert_chinese_plus_base | 298f3eb6ce959a8d191d608f85ba90b3e65740cf | 2021-07-07T01:18:40.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"zh",
"transformers",
"wobert",
"autotrain_compatible"
] | fill-mask | false | junnyu | null | junnyu/wobert_chinese_plus_base | 356 | 1 | transformers | 2,681 | ---
language: zh
tags:
- wobert
inference: False
---
## 介绍
### tf版本
https://github.com/ZhuiyiTechnology/WoBERT
### pytorch版本
https://github.com/JunnYu/WoBERT_pytorch
## 安装(主要为了安装WoBertTokenizer)
```bash
pip install git+https://github.com/JunnYu/WoBERT_pytorch.git
```
## 使用
```python
import torch
from transformers i... |
Helsinki-NLP/opus-mt-ht-en | c45c603fdf8b878d6002148783a21d85e5ece0b5 | 2021-09-09T22:10:28.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ht",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ht-en | 355 | null | transformers | 2,682 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ht-en
* source languages: ht
* target languages: en
* OPUS readme: [ht-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ht-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
google/multiberts-seed_13 | db04544bc9fe3a2c40fff2a460003e1a4d31c85f | 2021-11-05T22:31:43.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_13",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_13 | 355 | null | transformers | 2,683 | ---
language: en
tags:
- multiberts
- multiberts-seed_13
license: apache-2.0
---
# MultiBERTs - Seed 13
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://... |
raruidol/ArgumentRelation | eabc480c237123f0a4f9487d0872ec460d3c6b66 | 2022-01-26T15:04:12.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | raruidol | null | raruidol/ArgumentRelation | 355 | 1 | transformers | 2,684 | # Argument Relation Mining
Best performing model trained in the "Transformer-Based Models for Automatic Detection of Argument Relations: A Cross-Domain Evaluation" paper.
Code available in https://github.com/raruidol/ArgumentRelationMining
Cite:
```
@article{ruiz2021transformer,
title={Transformer-based... |
speechbrain/asr-wav2vec2-commonvoice-fr | 269ef5853401e2aa2e47fe6fd7027b067c630c9b | 2022-06-05T15:38:43.000Z | [
"wav2vec2",
"feature-extraction",
"fr",
"dataset:commonvoice",
"speechbrain",
"CTC",
"pytorch",
"Transformer",
"hf-asr-leaderboard",
"license:apache-2.0",
"automatic-speech-recognition",
"model-index"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-wav2vec2-commonvoice-fr | 355 | 5 | speechbrain | 2,685 | ---
language:
- fr
thumbnail: null
pipeline_tag: automatic-speech-recognition
tags:
- CTC
- pytorch
- speechbrain
- Transformer
- hf-asr-leaderboard
license: apache-2.0
datasets:
- commonvoice
metrics:
- wer
- cer
model-index:
- name: asr-wav2vec2-commonvoice-fr
results:
- task:
name: Automatic Speech Recogni... |
stanford-crfm/arwen-gpt2-medium-x21 | fc6844fbbbdc91bc63546c672282b8fb1d70b5d3 | 2022-06-20T11:36:44.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | stanford-crfm | null | stanford-crfm/arwen-gpt2-medium-x21 | 355 | null | transformers | 2,686 | Entry not found |
CAMeL-Lab/bert-base-arabic-camelbert-msa-ner | 54e2905e7c756883b00877cd48ed710a304af0d1 | 2021-10-17T11:07:13.000Z | [
"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-msa-ner | 354 | null | transformers | 2,687 | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT MSA NER Model
## Model description
**CAMeLBERT MSA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](h... |
SajjadAyoubi/xlm-roberta-large-fa-qa | 8e071d1d25324e15ebe203a245019e4e4f782e25 | 2021-04-21T07:23:30.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | SajjadAyoubi | null | SajjadAyoubi/xlm-roberta-large-fa-qa | 354 | null | transformers | 2,688 | ### How to use
#### Requirements
Transformers require `transformers` and `sentencepiece`, both of which can be
installed using `pip`.
```sh
pip install transformers sentencepiece
```
#### Pipelines 🚀
In case you are not familiar with Transformers, you can use pipelines instead.
Note that, pipelines can't have _no... |
microsoft/beit-large-finetuned-ade-640-640 | db2221bdd42a0f4c934ccd08a0eec10060ebd4d8 | 2022-02-22T09:08:30.000Z | [
"pytorch",
"beit",
"dataset:scene_parse_150",
"arxiv:2106.08254",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | microsoft | null | microsoft/beit-large-finetuned-ade-640-640 | 354 | null | transformers | 2,689 | ---
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_... |
norie4/DialoGPT-small-kyutebot | f0c0206ce3e265361c03fd0b84f4a09f1872210f | 2022-01-31T08:32:36.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | norie4 | null | norie4/DialoGPT-small-kyutebot | 354 | null | transformers | 2,690 | ---
tags:
- conversational
---
# mingbot DialoGPT Model |
Graphcore/gpt2-wikitext-103 | 2024fe13f55566bf24d75919f6880857beb1b537 | 2022-05-25T18:26:50.000Z | [
"pytorch",
"gpt2",
"text-generation",
"dataset:wikitext",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | Graphcore | null | Graphcore/gpt2-wikitext-103 | 354 | 1 | transformers | 2,691 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikitext
model-index:
- name: clm_output
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. -->
# Gra... |
Ahmad/parsT5-base | cfcb398d4d33113e3b8c63f15875e52c6be62077 | 2021-11-03T13:47:07.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Ahmad | null | Ahmad/parsT5-base | 353 | 3 | transformers | 2,692 | A monolingual T5 model for Persian trained on OSCAR 21.09 (https://oscar-corpus.com/) corpus with self-supervised method. 35 Gig deduplicated version of Persian data was used for pre-training the model.
It's similar to the English T5 model but just for Persian. You may need to fine-tune it on your specific task.
Exa... |
Contrastive-Tension/BERT-Base-Swe-CT-STSb | 7554c0a9f8abb8bc61193eb6cf26a243d586d565 | 2021-05-18T17:51:43.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | Contrastive-Tension | null | Contrastive-Tension/BERT-Base-Swe-CT-STSb | 353 | null | transformers | 2,693 | Entry not found |
google/multiberts-seed_15 | eff6de8f489d357cae470131562c20adadde6fb0 | 2021-11-05T22:35:05.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_15",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_15 | 353 | null | transformers | 2,694 | ---
language: en
tags:
- multiberts
- multiberts-seed_15
license: apache-2.0
---
# MultiBERTs - Seed 15
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://... |
HooshvareLab/bert-base-parsbert-armanner-uncased | 70a465658022ef6721ac95374b2bc38340d5fdc5 | 2021-05-18T20:42:28.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"fa",
"arxiv:2005.12515",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | HooshvareLab | null | HooshvareLab/bert-base-parsbert-armanner-uncased | 352 | null | transformers | 2,695 | ---
language: fa
license: apache-2.0
---
## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
Al... |
Laptop/DialoGPT-small-gandalf | 2e91521c0ec43d77db6447f26a9b3511b9f6c9ae | 2021-08-27T21:48:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Laptop | null | Laptop/DialoGPT-small-gandalf | 352 | null | transformers | 2,696 | ---
tags:
- conversational
---
# Gandalf DialoGPT Model |
google/multiberts-seed_14 | 3f10c679bb54bdcd581412d4f47a7fd589e41622 | 2021-11-05T22:33:27.000Z | [
"pytorch",
"tf",
"bert",
"pretraining",
"en",
"arxiv:2106.16163",
"arxiv:1908.08962",
"transformers",
"multiberts",
"multiberts-seed_14",
"license:apache-2.0"
] | null | false | google | null | google/multiberts-seed_14 | 352 | null | transformers | 2,697 | ---
language: en
tags:
- multiberts
- multiberts-seed_14
license: apache-2.0
---
# MultiBERTs - Seed 14
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://... |
huggingtweets/getfiscal | 761c0fe3c38033fe81940399fdd9963dffd48bc5 | 2021-05-22T05:24:29.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/getfiscal | 351 | null | transformers | 2,698 | ---
language: en
thumbnail: https://www.huggingtweets.com/getfiscal/1616662151704/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/116470978088510... |
puugz/DialoGPT-small-spiderman | 979eca1cebf1ae920bae64439d36aee8b6a62a24 | 2022-02-20T14:01:08.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | puugz | null | puugz/DialoGPT-small-spiderman | 351 | null | transformers | 2,699 | ---
tags:
- conversational
---
# Spider-Man DialoGPT Model |
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