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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
sdadas/polish-longformer-base-4096 | 848f1c0571529d428233937ac131d29ca30c2250 | 2022-03-08T17:58:15.000Z | [
"pytorch",
"longformer",
"fill-mask",
"transformers",
"license:lgpl-3.0",
"autotrain_compatible"
] | fill-mask | false | sdadas | null | sdadas/polish-longformer-base-4096 | 38 | null | transformers | 6,600 | ---
license: lgpl-3.0
---
|
mafeu/DialoGPT-medium-willem | dd01cff8fb370dac482a5cb5eee4963f7e8693c2 | 2022-03-11T05:15:26.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | mafeu | null | mafeu/DialoGPT-medium-willem | 38 | null | transformers | 6,601 | ---
tags:
- conversational
---
# willem DialoGPT Model |
Alvenir/bert-punct-restoration-en | 7b70ced9f319edea3e02a1d83c118a5b87d9ac04 | 2022-03-23T08:39:39.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | Alvenir | null | Alvenir/bert-punct-restoration-en | 38 | null | transformers | 6,602 | ---
license: apache-2.0
---
TODO |
hackathon-pln-es/paraphrase-spanish-distilroberta | 5ed9fdaabd705e7bd88029a3f08ce7397a666d6a | 2022-04-02T18:33:17.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"es",
"dataset:hackathon-pln-es/parallel-sentences",
"arxiv:2004.09813",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | hackathon-pln-es | null | hackathon-pln-es/paraphrase-spanish-distilroberta | 38 | 3 | sentence-transformers | 6,603 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
language:
- es
datasets:
- hackathon-pln-es/parallel-sentences
widget:
- text: "A ver si nos tenemos que poner todos en huelga hasta cobrar lo que queramos."
- text: "La huelga es el método de l... |
itaihay/wav2vec_asr_swbd | 048f809e7b5e62c0677617af12ef2f6111bf992d | 2022-05-21T20:37:08.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | itaihay | null | itaihay/wav2vec_asr_swbd | 38 | null | transformers | 6,604 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec_asr_swbd
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. -->
# wav2vec_asr_swbd
... |
Helsinki-NLP/opus-mt-tc-big-zls-en | 7aab35f8931e35023d23bd43fec94e189bf8c073 | 2022-06-01T12:58:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bg",
"bs_Latn",
"en",
"hr",
"mk",
"sh",
"sl",
"sr_Cyrl",
"sr_Latn",
"zls",
"transformers",
"translation",
"opus-mt-tc",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tc-big-zls-en | 38 | null | transformers | 6,605 | ---
language:
- bg
- bs_Latn
- en
- hr
- mk
- sh
- sl
- sr_Cyrl
- sr_Latn
- zls
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-zls-en
results:
- task:
name: Translation bul-eng
type: translation
args: bul-eng
dataset:
name: flores101-devtest
... |
NTUYG/ComFormer | f9d442b8ba969018a873c406709d33caf64ed394 | 2022-05-09T10:55:14.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:DeepCom",
"arxiv:2107.03644",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | NTUYG | null | NTUYG/ComFormer | 38 | null | transformers | 6,606 | ---
language:
- en
tags:
- summarization
license: apache-2.0
datasets:
- DeepCom
metrics:
- bleu
---
# How To Use
```PYTHON
from transformers import BartForConditionalGeneration, BartTokenizer
model = BartForConditionalGeneration.from_pretrained("NTUYG/ComFormer")
tokenizer = BartTokenizer.from_pretrained("NTUYG/ComFo... |
BitanBiswas/wav2vec2-base-timit-demo-google-colab | a5ebbb51fbcb749c3c1f183ed90e7fee8a99535c | 2022-05-14T07:46:48.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | BitanBiswas | null | BitanBiswas/wav2vec2-base-timit-demo-google-colab | 38 | null | transformers | 6,607 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-timit-demo-google-colab
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. -->
... |
Anjoe/german-poetry-gpt2 | 62ceddc7716eabfd104604277bc18fd10f6ffc4f | 2022-06-08T14:59:08.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | Anjoe | null | Anjoe/german-poetry-gpt2 | 38 | null | transformers | 6,608 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: german-poetry-gpt2
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. -->
# german-poetry-gpt2
Thi... |
alibaba-pai/pai-bert-base-zh | 8960eef5606b0034b3b21afc5d0534d5ec491539 | 2022-06-10T02:35:32.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"arxiv:2205.00258",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | alibaba-pai | null | alibaba-pai/pai-bert-base-zh | 38 | 1 | transformers | 6,609 | ---
language: zh
pipeline_tag: fill-mask
tags:
- bert
license: apache-2.0
---
## Alibaba PAI BERT Base Chinese
This project provides Chinese pre-trained language models and various types of NLP tools. The models are pre-trained on the large-scale corpora hosted by the Alibaba PAI team. It is developed based on the Ea... |
Tonjk/wangchanberta-base-att-spm-uncased | 993b181e83d9eb76ee45aae2c077fcbc4ef79c88 | 2022-07-09T18:36:41.000Z | [
"pytorch",
"tensorboard",
"camembert",
"fill-mask",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | Tonjk | null | Tonjk/wangchanberta-base-att-spm-uncased | 38 | null | transformers | 6,610 | ---
tags:
- generated_from_trainer
model-index:
- name: wangchanberta-base-att-spm-uncased
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. -->
# wangchanberta-base-a... |
Lemswasabi/xlsr-53-tuudle-14h-with-lm-4g | 9d5276ad811f3e912a991dacdb5d65405bac8064 | 2022-07-10T18:24:35.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | Lemswasabi | null | Lemswasabi/xlsr-53-tuudle-14h-with-lm-4g | 38 | null | transformers | 6,611 | Entry not found |
matanbn/smsPhishing | 2a6a11a4983b899d12a57f320a973e210dc74ed4 | 2022-07-18T14:17:25.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | matanbn | null | matanbn/smsPhishing | 38 | null | transformers | 6,612 | Entry not found |
naver-clova-ix/donut-base-finetuned-zhtrainticket | 2d3fed6b7075870ec620a35d74efd2920636f352 | 2022-07-19T14:57:51.000Z | [
"pytorch",
"donut",
"transformers",
"license:mit"
] | null | false | naver-clova-ix | null | naver-clova-ix/donut-base-finetuned-zhtrainticket | 38 | null | transformers | 6,613 | ---
license: mit
---
|
TeaTM/DialoGPT-large-bushcat | 08d0fc23e3995cbafefb3b860316235ecf525b2a | 2022-07-21T17:40:29.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | TeaTM | null | TeaTM/DialoGPT-large-bushcat | 38 | null | transformers | 6,614 | ---
tags:
- conversational
---
# Bushcat DialoGPT-Large Model |
51la5/XSUM-keyphrase-gen | 3759bc51223abaff7b5738690f18298883f74638 | 2022-07-22T10:26:02.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | 51la5 | null | 51la5/XSUM-keyphrase-gen | 38 | null | transformers | 6,615 | Entry not found |
IDEA-CCNL/Erlangshen-ZEN1-224M-Chinese | 374c3b6559b0ff8df0f86978d7c24063148049c9 | 2022-07-27T06:07:26.000Z | [
"pytorch",
"zh",
"transformers",
"ZEN",
"chinese",
"license:apache-2.0"
] | null | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-ZEN1-224M-Chinese | 38 | null | transformers | 6,616 | ---
language:
- zh
license: apache-2.0
tags:
- ZEN
- chinese
inference: false
---
# Erlangshen-ZEN1-224M-Chinese, one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
Erlangshen-ZEN1-224M-Chinese is an open-source Chinese pre-training model of the ZEN team on the [Fengshenbang-LM](https:... |
Finnish-NLP/gpt2-medium-finnish | e34f06fc20e97d3f07125e176e8d5a965cb522ed | 2022-06-13T16:14:13.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"transformers",
"finnish",
"license:apache-2.0"
] | text-generation | false | Finnish-NLP | null | Finnish-NLP/gpt2-medium-finnish | 37 | 2 | transformers | 6,617 | ---
language:
- fi
license: apache-2.0
tags:
- finnish
- gpt2
datasets:
- Finnish-NLP/mc4_fi_cleaned
- wikipedia
widget:
- text: "Tekstiä tuottava tekoäly on"
---
# GPT-2 medium for Finnish
Pretrained GPT-2 medium model on Finnish language using a causal language modeling (CLM) objective. GPT-2 was introduced in
[th... |
Helsinki-NLP/opus-mt-en-kg | 13e60125596c4f07a3b02dcd38caff5f334bec4c | 2021-09-09T21:36:33.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"kg",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-kg | 37 | null | transformers | 6,618 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-kg
* source languages: en
* target languages: kg
* OPUS readme: [en-kg](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-kg/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-en-nso | 72a24d292415856a91b71ec1fbf9bc37e4bb691d | 2021-09-09T21:38:10.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"nso",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-nso | 37 | null | transformers | 6,619 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-nso
* source languages: en
* target languages: nso
* OPUS readme: [en-nso](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-nso/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-en-zlw | 1a4faff7e8d9673adc6517e1e54a7d2938d35e23 | 2021-01-18T08:19:43.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"pl",
"cs",
"zlw",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-zlw | 37 | null | transformers | 6,620 | ---
language:
- en
- pl
- cs
- zlw
tags:
- translation
license: apache-2.0
---
### eng-zlw
* source group: English
* target group: West Slavic languages
* OPUS readme: [eng-zlw](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-zlw/README.md)
* model: transformer
* source language(s): e... |
Helsinki-NLP/opus-mt-hil-en | de7ad57b834519e8ee9f3eb9a96b2a546709acf9 | 2021-09-09T22:10:02.000Z | [
"pytorch",
"marian",
"text2text-generation",
"hil",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-hil-en | 37 | null | transformers | 6,621 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-hil-en
* source languages: hil
* target languages: en
* OPUS readme: [hil-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/hil-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-no-fr | 00ad8c45b62b5a7e8815dbdb02d1c84edb0e551e | 2020-08-21T14:42:48.000Z | [
"pytorch",
"marian",
"text2text-generation",
"no",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-no-fr | 37 | null | transformers | 6,622 | ---
language:
- no
- fr
tags:
- translation
license: apache-2.0
---
### nor-fra
* source group: Norwegian
* target group: French
* OPUS readme: [nor-fra](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/nor-fra/README.md)
* model: transformer-align
* source language(s): nno nob
* target la... |
Helsinki-NLP/opus-mt-sv-es | 3c50d646c512d4e553ac53ae0a584291eeaee659 | 2021-09-10T14:06:15.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sv",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sv-es | 37 | null | transformers | 6,623 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sv-es
* source languages: sv
* target languages: es
* OPUS readme: [sv-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sv-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-sv-fi | 933c6ce27c572414033f42cf5c898334071c497a | 2021-09-10T14:06:23.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sv",
"fi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sv-fi | 37 | null | transformers | 6,624 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sv-fi
* source languages: sv
* target languages: fi
* OPUS readme: [sv-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sv-fi/README.md)
* dataset: opus+bt
* model: transformer-align
* pre-processing: normalization + SentencePiece
* do... |
IDEA-CCNL/Zhouwenwang-Unified-110M | 87a08517e6f355808aee9d1faad6cd5399b75977 | 2022-04-12T01:59:26.000Z | [
"pytorch",
"megatron-bert",
"zh",
"transformers",
"license:apache-2.0"
] | null | false | IDEA-CCNL | null | IDEA-CCNL/Zhouwenwang-Unified-110M | 37 | 2 | transformers | 6,625 | ---
language:
- zh
license: apache-2.0
widget:
- text: "生活的真谛是[MASK]。"
---
# Zhouwenwang-Unified-110M model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
Zhouwenwang-Unified-110M apply a new unified structure, and jointly developed by the IDEA-CCNL and Zhuiyi Technology. In ... |
Laeyoung/BTS-comments-generator | 5f7d12030bd3e1cfdd4c31eff1b4af79dfa5bda8 | 2021-06-08T07:59:07.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | Laeyoung | null | Laeyoung/BTS-comments-generator | 37 | null | transformers | 6,626 | ### Model information
* Fine tuning dataset: https://www.kaggle.com/seungguini/bts-youtube-comments
* Base model: GPT2 Small
* Epoch: 5
* API page: [Ainize](https://ainize.ai/teachable-ainize/gpt2-train?branch=train/cv695m9g40av0cdabuqp)
* Demo page: [End-point](https://kubecon-tabtab-ainize-team.endpoint.ainize.ai/?mo... |
Michael711/feinschwarz | d7dcef9f70eaeffd4b09cc9737c9d1fc542b4220 | 2021-10-27T18:28:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"de",
"license:mit",
"model-index"
] | text-generation | false | Michael711 | null | Michael711/feinschwarz | 37 | null | transformers | 6,627 | ---
license: mit
tags:
- generated_from_trainer
- de
model-index:
- name: feinesblack
results: []
---
# feinschwarz
This model is a fine-tuned version of [dbmdz/german-gpt2](https://huggingface.co/dbmdz/german-gpt2). The dataset was compiled from all texts of https://www.feinschwarz.net (as of October 2021). The h... |
RabotaRu/HRBert-mini | 5a941ea031c513dec885ae38829963c0899066e5 | 2021-12-03T10:55:36.000Z | [
"pytorch",
"roberta",
"fill-mask",
"ru",
"en",
"be",
"bg",
"uk",
"ro",
"kz",
"tg",
"tat",
"sv",
"sl",
"sr",
"uz",
"es",
"fi",
"transformers",
"russian",
"pretraining",
"embeddings",
"masked-lm",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | RabotaRu | null | RabotaRu/HRBert-mini | 37 | 3 | transformers | 6,628 | ---
language: ["ru", "en", "be", "bg", "uk", "ro", "kz", "tg", "tat", "sv", "sl", "sr", "uz", "es", "fi"]
tags:
- russian
- fill-mask
- pretraining
- embeddings
- masked-lm
license: mit
widget:
- text: "<mask> на склад"
---
!!!
At the moment, the model is distilled, a version from one of the first checkpo... |
Roberta55/deberta-base-mnli-finetuned-cola | c3d249fc84118ce311e1f1c7d110b212caf13442 | 2021-10-21T09:07:56.000Z | [
"pytorch",
"tensorboard",
"deberta",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | Roberta55 | null | Roberta55/deberta-base-mnli-finetuned-cola | 37 | null | transformers | 6,629 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: deberta-base-mnli-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
- n... |
VoVanPhuc/unsup-SimCSE-VietNamese-phobert-base | fa3b072f1e5cc0de5addaad4cdcc22d7eb175ab5 | 2021-05-28T05:45:41.000Z | [
"pytorch",
"roberta",
"arxiv:2104.08821",
"transformers"
] | null | false | VoVanPhuc | null | VoVanPhuc/unsup-SimCSE-VietNamese-phobert-base | 37 | null | transformers | 6,630 |
#### Table of contents
1. [Introduction](#introduction)
2. [Pretrain model](#models)
3. [Using SimeCSE_Vietnamese with `sentences-transformers`](#sentences-transformers)
- [Installation](#install1)
- [Example usage](#usage1)
4. [Using SimeCSE_Vietnamese with `transformers`](#transformers)
- [Installation](#install2... |
arvalinno/distilbert-base-uncased-finetuned-indosquad-v2 | 421ce963a1c39e1be5f7706b429619cb7603a05e | 2021-11-21T04:15:31.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | arvalinno | null | arvalinno/distilbert-base-uncased-finetuned-indosquad-v2 | 37 | null | transformers | 6,631 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-indosquad-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, then remove this comm... |
castorini/duot5-3b-msmarco | 72c531606da1a625c9060d3e8ac1cf2157c7dcf3 | 2021-05-28T11:51:36.000Z | [
"pytorch",
"t5",
"feature-extraction",
"arxiv:2101.05667",
"transformers"
] | feature-extraction | false | castorini | null | castorini/duot5-3b-msmarco | 37 | null | transformers | 6,632 | This model is a T5-3B reranker, initialized with our pointwise ranker, [castorini/monot5-3b-msmarco](https://huggingface.co/castorini/monot5-3b-msmarco), and finetuned on the MS MARCO passage dataset for 50K steps (or 5 epochs) on the pairwise reranking task.
For more details on how to use it, check [pygaggle.ai](pyga... |
cimm-kzn/enrudr-bert | e1ecd42e660a377a2ae5f8a608afeb4c5fa75675 | 2020-12-11T21:35:46.000Z | [
"pytorch",
"ru",
"en",
"arxiv:2004.03659",
"transformers"
] | null | false | cimm-kzn | null | cimm-kzn/enrudr-bert | 37 | null | transformers | 6,633 | ---
language:
- ru
- en
---
## EnRuDR-BERT
EnRuDR-BERT - Multilingual, Cased, which pretrained on the raw part of the RuDReC corpus (1.4M reviews) and english collection of consumer comments on drug administration from [2]. Pre-training was based on the [original BERT code](https://github.com/google-research/bert) pro... |
echarlaix/bert-large-uncased-whole-word-masking-finetuned-sst-2 | cad77115b29db5fcb25ef6b6ff5da941dd614d31 | 2021-05-19T16:48:31.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | echarlaix | null | echarlaix/bert-large-uncased-whole-word-masking-finetuned-sst-2 | 37 | null | transformers | 6,634 | Entry not found |
enelpi/bert-question-answering-uncased-squadv2_tr | 058ac980155af602e15d7dafdfee7c275c0eb826 | 2021-05-19T16:28:28.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | enelpi | null | enelpi/bert-question-answering-uncased-squadv2_tr | 37 | null | transformers | 6,635 | Entry not found |
flax-community/clip-rsicd | 8357af47297adf43a37a88e424a7cfffc04ec95c | 2022-04-24T21:02:26.000Z | [
"pytorch",
"jax",
"clip",
"feature-extraction",
"transformers",
"vision"
] | feature-extraction | false | flax-community | null | flax-community/clip-rsicd | 37 | null | transformers | 6,636 | ---
tags:
- vision
---
# Model Card: clip-rsicd
## Model Details
This model is a finetuned [CLIP by OpenAI](https://huggingface.co/openai/clip-vit-base-patch32). It is designed with an aim to improve zero-shot image classification, text-to-image and image-to-image retrieval specifically on remote sensing images.
##... |
google/roberta2roberta_L-24_gigaword | eed8e81a8b45221556517f48b0e6e40e70006111 | 2020-12-11T21:43:15.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"en",
"dataset:gigaword",
"arxiv:1907.12461",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | google | null | google/roberta2roberta_L-24_gigaword | 37 | null | transformers | 6,637 | ---
language: en
license: apache-2.0
datasets:
- gigaword
tags:
- summarization
---
# Roberta2Roberta_L-24_gigaword EncoderDecoder model
The model was introduced in
[this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.d... |
healx/biomedical-slot-filling-reader-base | b1ad1e5d67113f0e25a9d9a9b8a9732db8cec6eb | 2021-11-16T09:16:36.000Z | [
"pytorch",
"bert",
"question-answering",
"arxiv:2109.08564",
"transformers",
"autotrain_compatible"
] | question-answering | false | healx | null | healx/biomedical-slot-filling-reader-base | 37 | null | transformers | 6,638 | Reader model for Biomedical slot filling see https://arxiv.org/abs/2109.08564 for details. The model is initialized with [biobert-base](https://huggingface.co/dmis-lab/biobert-v1.1). |
it5/it5-small-news-summarization | b619de1c052990b8a503dc8013165a1267ba08a9 | 2022-03-09T07:52:53.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:ARTeLab/fanpage",
"dataset:ARTeLab/ilpost",
"arxiv:2203.03759",
"transformers",
"italian",
"sequence-to-sequence",
"fanpage",
"ilpost",
"summarization",
"license:apache-2.0",
"model-index",
"co2_e... | summarization | false | it5 | null | it5/it5-small-news-summarization | 37 | 1 | transformers | 6,639 | ---
language:
- it
license: apache-2.0
datasets:
- ARTeLab/fanpage
- ARTeLab/ilpost
tags:
- italian
- sequence-to-sequence
- fanpage
- ilpost
- summarization
widget:
- text: "Non lo vuole sposare. E’ quanto emerge all’interno dell’ultima intervista di Raffaella Fico che, ringraziando Mancini per i buoni consigli elargi... |
kazandaev/opus-mt-ru-en-finetuned | 726f655b41154c21283acf053dce87166789e608 | 2022-02-27T20:47:54.000Z | [
"pytorch",
"tensorboard",
"rust",
"marian",
"text2text-generation",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | kazandaev | null | kazandaev/opus-mt-ru-en-finetuned | 37 | null | transformers | 6,640 | ---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-ru-en-finetuned
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. -->
# opus-mt-ru-en-f... |
kuppuluri/telugu_bertu | b47dda16f5ba373e547b3a41b4410a219e20f7ff | 2021-12-02T18:14:46.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"te",
"transformers",
"autotrain_compatible"
] | fill-mask | false | kuppuluri | null | kuppuluri/telugu_bertu | 37 | 2 | transformers | 6,641 | ---
language: te
---
# telugu_bertu
## Model description
This model is a BERT MLM model trained on Telugu. Please use it from the terminal as the web interface has encoding issues.
PS: If you find my model useful, I would appreciate a note from you as it would encourage me to continue improving it and also add new m... |
lordtt13/blenderbot_small-news | 1599591fbf90efc193aeebcd2a3a28955f56e745 | 2021-02-11T08:21:09.000Z | [
"pytorch",
"tf",
"blenderbot-small",
"text2text-generation",
"en",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | lordtt13 | null | lordtt13/blenderbot_small-news | 37 | null | transformers | 6,642 | ---
language: en
---
## BlenderBotSmall-News: Small version of a state-of-the-art open source chatbot, trained on custom summaries
### Details of BlenderBotSmall
The **BlenderBotSmall** model was presented in [A state-of-the-art open source chatbot](https://ai.facebook.com/blog/state-of-the-art-open-source-chatbot/)... |
megagonlabs/t5-base-japanese-web-8k | 9b69d115ad51cd03338a0d26cccc29c5a3bb30d5 | 2021-09-06T10:31:50.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ja",
"dataset:mc4",
"dataset:wiki40b",
"arxiv:1910.10683",
"transformers",
"seq2seq",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | megagonlabs | null | megagonlabs/t5-base-japanese-web-8k | 37 | 1 | transformers | 6,643 | ---
language: ja
tags:
- t5
- text2text-generation
- seq2seq
license: apache-2.0
datasets:
- mc4
- wiki40b
---
# t5-base-japanese-web (with Byte-fallback, 8K)
## Description
[megagonlabs/t5-base-japanese-web](https://huggingface.co/megagonlabs/t5-base-japanese-web) is a T5 (Text-to-Text Transfer Transformer) model p... |
mrm8488/spanbert-base-finetuned-squadv2 | c4abebca5cf02dc3812a7f34004146ed28a93c35 | 2021-05-20T00:51:05.000Z | [
"pytorch",
"jax",
"bert",
"en",
"arxiv:1907.10529",
"transformers"
] | null | false | mrm8488 | null | mrm8488/spanbert-base-finetuned-squadv2 | 37 | null | transformers | 6,644 | ---
language: en
thumbnail:
---
# SpanBERT base fine-tuned on SQuAD v2
[SpanBERT](https://github.com/facebookresearch/SpanBERT) created by [Facebook Research](https://github.com/facebookresearch) and fine-tuned on [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) for **Q&A** downstream task ([by them](https://... |
mrm8488/spanbert-large-finetuned-tacred | 0a7170618e7eccb43a61ff24d58b8c65c266f4fc | 2021-05-20T01:01:51.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"en",
"arxiv:1907.10529",
"transformers"
] | feature-extraction | false | mrm8488 | null | mrm8488/spanbert-large-finetuned-tacred | 37 | null | transformers | 6,645 | ---
language: en
thumbnail:
---
# SpanBERT large fine-tuned on TACRED
[SpanBERT](https://github.com/facebookresearch/SpanBERT) created by [Facebook Research](https://github.com/facebookresearch) and fine-tuned on [TACRED](https://nlp.stanford.edu/projects/tacred/) dataset by [them](https://github.com/facebookresearch... |
persiannlp/mt5-base-parsinlu-arc-comqa-obqa-multiple-choice | cd15568d1ad33eaed099e67ae3b1eb2947e43008 | 2021-09-23T16:19:52.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"dataset:commonsenseqa",
"dataset:arc",
"dataset:openbookqa",
"transformers",
"multiple-choice",
"mt5",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-base-parsinlu-arc-comqa-obqa-multiple-choice | 37 | null | transformers | 6,646 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- multiple-choice
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- commonsenseqa
- arc
- openbookqa
metrics:
- accuracy
---
# Multiple-Choice Question Answering (مدل برای پاسخ به سوال... |
pysentimiento/robertuito-base-cased | ad3aad808a26dd2208003e8068137cbd40c4ad1b | 2021-11-19T13:57:43.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2111.09453",
"transformers",
"autotrain_compatible"
] | fill-mask | false | pysentimiento | null | pysentimiento/robertuito-base-cased | 37 | null | transformers | 6,647 | # robertuito-base-cased
**WORK IN PROGRESS**
# RoBERTuito
## A pre-trained language model for social media text in Spanish
[**READ THE FULL PAPER**](https://arxiv.org/abs/2111.09453)
[Github Repository](https://github.com/pysentimiento/robertuito)
*RoBERTuito* is a pre-trained language model for user-generated conte... |
sbrandeis/autonlp-emotion-clf | 2a2378d1f2fba68c5a87cd285df488a69ff72e71 | 2021-12-07T08:16:13.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:sbrandeis/autonlp-data-emotion-classification-pre",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | sbrandeis | null | sbrandeis/autonlp-emotion-clf | 37 | null | transformers | 6,648 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- sbrandeis/autonlp-data-emotion-classification-pre
co2_eq_emissions: 23.4692320403666
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 3252433
- CO2 Emissions (in grams): 23.4692320403666
## Validati... |
textattack/albert-base-v2-RTE | 4a2a6a5abfc24d88d493e0df81de4c9192d88793 | 2020-07-06T16:31:05.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/albert-base-v2-RTE | 37 | null | transformers | 6,649 | ## TextAttack Model Card
This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 64, a learning
rate of 3e-05, and a maximum sequence length of 128.
Since this was a classi... |
valhalla/cogview-gpt2-test | 8d82689e18f46530c080a35c69097e56c8e62557 | 2021-06-21T07:00:17.000Z | [
"pytorch",
"cog_view",
"text-generation",
"transformers"
] | text-generation | false | valhalla | null | valhalla/cogview-gpt2-test | 37 | null | transformers | 6,650 | Entry not found |
w11wo/wav2vec2-xls-r-300m-korean | 72ac2f064315c4ab807c8a59ce1ce17536c1d520 | 2022-03-23T18:26:14.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"ko",
"dataset:kresnik/zeroth_korean",
"arxiv:2111.09296",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | w11wo | null | w11wo/wav2vec2-xls-r-300m-korean | 37 | null | transformers | 6,651 | ---
language: ko
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- kresnik/zeroth_korean
model-index:
- name: Wav2Vec2 XLS-R 300M Korean
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recog... |
yobi/klue-roberta-base-ynat | 1f8ec1e7ee4ed746829a663b9879fae1b4602231 | 2021-06-26T15:57:17.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | yobi | null | yobi/klue-roberta-base-ynat | 37 | null | transformers | 6,652 | |
yseop/roberta-base-finance-hypernym-identification | 18381a24f6aa39417a7baa4fb1ff2560faa2ced9 | 2021-07-16T22:50:30.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | yseop | null | yseop/roberta-base-finance-hypernym-identification | 37 | 5 | sentence-transformers | 6,653 | ---
inference: false
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
<div style="clear: both;">
<div style="float: left; margin-right 1em;">
<h1><strong>FinISH (Finance-Identifying Sroberta for Hypernyms)</strong></h1>
</div>
<div>... |
zhuqing/bert-base-uncased-reddit-business-v2 | 5af3dacba3726ec11b6b43bf23d4cfc418abfedb | 2021-08-03T06:15:56.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | zhuqing | null | zhuqing/bert-base-uncased-reddit-business-v2 | 37 | null | transformers | 6,654 | Entry not found |
microsoft/tapex-large-finetuned-tabfact | 690c413ce530ea49370b5f4fe452ce2628460e1e | 2022-07-14T10:10:10.000Z | [
"pytorch",
"bart",
"text-classification",
"en",
"dataset:tab_fact",
"arxiv:2107.07653",
"transformers",
"tapex",
"table-question-answering",
"license:mit"
] | text-classification | false | microsoft | null | microsoft/tapex-large-finetuned-tabfact | 37 | null | transformers | 6,655 | ---
language: en
tags:
- tapex
- table-question-answering
datasets:
- tab_fact
license: mit
---
# TAPEX (large-sized model)
TAPEX was proposed in [TAPEX: Table Pre-training via Learning a Neural SQL Executor](https://arxiv.org/abs/2107.07653) by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, J... |
zhufy/squad-ms-bert-base | 61d4fd76fed22f66185a866c500b40ac77b3465b | 2022-04-23T05:09:03.000Z | [
"pytorch",
"bert",
"question-answering",
"Malay",
"dataset:Malay SQuAD",
"transformers",
"bert-base",
"autotrain_compatible"
] | question-answering | false | zhufy | null | zhufy/squad-ms-bert-base | 37 | null | transformers | 6,656 | ---
language: Malay
task: extractive question answering
datasets: Malay SQuAD
tags:
- bert-base
---
# Model Description
This model is for Malay extractive question answering. It is based on the [malay-huggingface/bert-base-bahasa-cased](https://huggingface.co/malay-huggingface/bert-base-bahasa-cased/tree/main) model... |
mrm8488/electricidad-small-finetuned-amazon-review-classification | cbaeb0d04ba55182b54925e2520318ef320757a5 | 2022-03-14T15:10:38.000Z | [
"pytorch",
"tensorboard",
"electra",
"text-classification",
"dataset:amazon_reviews_multi",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | mrm8488 | null | mrm8488/electricidad-small-finetuned-amazon-review-classification | 37 | null | transformers | 6,657 | ---
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
widget:
- text: "me parece muy mal , se salía el producto por la caja y venían vacios , lo devolvere"
- text: "Correa de buena calidad, con un interior oscuro. Cumple perfectamente su función y se intercambia fácilmente. Una buena opción para cambiar e... |
canwenxu/laprador | 0ba3b6b7b7327bf3956b1bb6d8a20ac35cfaf44c | 2022-04-25T08:13:10.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"arxiv:2203.06169",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | canwenxu | null | canwenxu/laprador | 37 | 1 | transformers | 6,658 | ---
license: apache-2.0
---
# 🦮 LaPraDoR
Pretrained checkpoint for Findings of ACL 2022 paper [LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval](https://arxiv.org/abs/2203.06169).
To use this model, please refer to our [GitHub repo](https://github.com/JetRunner/LaPraDoR).
|
abdelrahmanzied/bert-fake-news-classifier | 37cbbc55de57a13d08f94d4e57829848f8106ca1 | 2022-04-01T16:40:56.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | abdelrahmanzied | null | abdelrahmanzied/bert-fake-news-classifier | 37 | null | transformers | 6,659 | ---
license: mit
---
|
nickil/real-fake-news | 9c8e1012fb30fb2ecfe01cd56c58c81d2ab56976 | 2022-04-07T05:50:48.000Z | [
"pytorch",
"longformer",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | nickil | null | nickil/real-fake-news | 37 | null | transformers | 6,660 | ---
license: mit
---
Data: [https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset](https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset) |
palakagl/bert_MultiClass_TextClassification | be52ae7f69b8bda1a0bc94b96fe5200c358296c1 | 2022-04-07T17:06:55.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:palakagl/autotrain-data-PersonalAssitant",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | palakagl | null | palakagl/bert_MultiClass_TextClassification | 37 | null | transformers | 6,661 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- palakagl/autotrain-data-PersonalAssitant
co2_eq_emissions: 5.080390550458655
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 717221775
- CO2 Emissions (in grams): 5.080390550458655
## Validat... |
patrickvonplaten/wav2vec2-base-960h-4-gram | edb5c3d28f5851632687c9de5826744fecfc9176 | 2022-05-24T11:09:47.000Z | [
"pytorch",
"tf",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"transformers",
"audio",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-base-960h-4-gram | 37 | null | transformers | 6,662 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.huggingface.... |
Intel/bart-large-mrpc | 79930c8973deb7fb3a3c72fd040b336e2c3d267e | 2022-04-21T08:11:16.000Z | [
"pytorch",
"bart",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Intel | null | Intel/bart-large-mrpc | 37 | null | transformers | 6,663 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bart-large-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
... |
clips/republic | ef602ad12874e6db4edb465d63db1d1b5c5967c3 | 2022-06-10T09:06:29.000Z | [
"pytorch",
"bert",
"text-classification",
"nl",
"transformers",
"text classification",
"sentiment analysis",
"domain adaptation"
] | text-classification | false | clips | null | clips/republic | 37 | null | transformers | 6,664 | ---
pipeline_tag: text-classification
language:
- nl
tags:
- text classification
- sentiment analysis
- domain adaptation
widget:
- text: "De NMBS heeft recent de airconditioning in alle treinen vernieuwd."
example_title: "POS-NMBS"
- text: "De wegenwerken langs de E34 blijven al maanden aanhouden."
exam... |
JeffreyLau/SikuGPT2-poem | c9030badb2883ff86f6e3eda4956d19b81e7587f | 2022-07-10T01:29:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"zh",
"transformers"
] | text-generation | false | JeffreyLau | null | JeffreyLau/SikuGPT2-poem | 37 | 2 | transformers | 6,665 | ---
language: zh
widget:
- text: "[CLS] 明 月 幾 時 有 ，"
- text: "[CLS] 大 漠 孤 烟 直 ，"
- text: "[CLS] 李 白 乘 舟 將 慾 行 ，"
max_length: 50
---
# SikuGPT2-Poem Model
## Model description
The model is used to generate Chinese ancient poems. You can download the model via HuggingFace from the link [SikuGPT2-poem](https://hugg... |
BaxterAI/SentimentClassifier | 1c27a5dfd4aee05b8ac858a107b9d87128eff6ea | 2022-05-25T04:28:53.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:amazon_polarity",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | BaxterAI | null | BaxterAI/SentimentClassifier | 37 | null | transformers | 6,666 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_polarity
metrics:
- accuracy
- f1
model-index:
- name: SentimentClassifier
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_polarity
type: amazon_polarity
args: amazo... |
KoichiYasuoka/deberta-base-thai-upos | fa4a2482cc1692deb3c4bc5e7402a42bdc07755e | 2022-05-29T10:45:44.000Z | [
"pytorch",
"deberta-v2",
"token-classification",
"th",
"dataset:universal_dependencies",
"transformers",
"thai",
"pos",
"wikipedia",
"dependency-parsing",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/deberta-base-thai-upos | 37 | null | transformers | 6,667 | ---
language:
- "th"
tags:
- "thai"
- "token-classification"
- "pos"
- "wikipedia"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "apache-2.0"
pipeline_tag: "token-classification"
widget:
- text: "หลายหัวดีกว่าหัวเดียว"
---
# deberta-base-thai-upos
## Model Description
This is a DeBERTa(V2) mod... |
ITESM/st_demo_6 | 7ba6e49bac6dc1f197919b007d9b98bd995e6a8f | 2022-06-05T05:06:07.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"es",
"dataset:hackathon-pln-es/nli-es",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity"
] | sentence-similarity | false | ITESM | null | ITESM/st_demo_6 | 37 | null | sentence-transformers | 6,668 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
language:
- es
datasets:
- hackathon-pln-es/nli-es
widget:
- text: "A ver si nos tenemos que poner todos en huelga hasta cobrar lo que queramos."
- text: "La huelga es el método de lucha más eficaz para conseg... |
ajtamayoh/NLP-CIC-WFU_Clinical_Cases_NER_Sents_tokenized_mBERT_cased_fine_tuned | 37fbf10d51fa4f6ff0a6bdf1d82c9e48fd99527d | 2022-06-14T16:25:05.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | ajtamayoh | null | ajtamayoh/NLP-CIC-WFU_Clinical_Cases_NER_Sents_tokenized_mBERT_cased_fine_tuned | 37 | null | transformers | 6,669 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-CIC-WFU_Clinical_Cases_NER_Sents_tokenized_mBERT_cased_fine_tuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to.... |
waboucay/camembert-large-finetuned-rua_wl_3_classes | 83afb9e9ef5a40f261a69fe441dbc18c120e74e5 | 2022-06-19T14:35:04.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"transformers",
"nli"
] | text-classification | false | waboucay | null | waboucay/camembert-large-finetuned-rua_wl_3_classes | 37 | null | transformers | 6,670 | ---
language:
- fr
tags:
- nli
metrics:
- f1
---
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 75.3 | 74.9 |
| test ... |
Supreeth/Toxic-XLM_RoBERTa | dad6a5f6ec12bbae449053e2d175172a69e1145f | 2022-06-20T13:21:10.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers",
"license:afl-3.0"
] | text-classification | false | Supreeth | null | Supreeth/Toxic-XLM_RoBERTa | 37 | null | transformers | 6,671 | ---
license: afl-3.0
---
|
climabench/miniLM-cdp-all | c6805859ce8567ef523dfc3aa6804e4fcef63bbf | 2022-06-25T09:58:21.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | climabench | null | climabench/miniLM-cdp-all | 37 | null | transformers | 6,672 | Entry not found |
f00d/Multilingual-MiniLM-L12-H384-CLM-finetuned-wikipedia_bn | bee036fe2f6c4a30cdd21b1cc4099fc2a96039e0 | 2022-07-07T11:10:04.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | f00d | null | f00d/Multilingual-MiniLM-L12-H384-CLM-finetuned-wikipedia_bn | 37 | null | transformers | 6,673 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: Multilingual-MiniLM-L12-H384-CLM-finetuned-wikipedia_bn
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 co... |
pnichite/YTFineTuneBert | bbe87bc09965f437992b70efb70fed4f03e92614 | 2022-07-09T17:46:05.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pnichite | null | pnichite/YTFineTuneBert | 37 | null | transformers | 6,674 | Entry not found |
zhernosek12/classif_sasha | 7a29f8eef716e4c14b358f8e9d8fd1773406535c | 2022-07-13T14:48:37.000Z | [
"pytorch",
"layoutlmv2",
"text-classification",
"transformers"
] | text-classification | false | zhernosek12 | null | zhernosek12/classif_sasha | 37 | null | transformers | 6,675 | Entry not found |
sam34738/xlm-roberta-hindi-nisha | 69b0cc16c8290ba791c7aae0adb726261be4ca9a | 2022-07-14T09:40:30.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | sam34738 | null | sam34738/xlm-roberta-hindi-nisha | 37 | null | transformers | 6,676 | ---
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-hindi-nisha
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. -->
# xlm-roberta-hindi-nisha
This m... |
IDEA-CCNL/Erlangshen-Deberta-97M-Chinese | ad248fffb7a0a2536f5bb8a9aaee3faf39ee212b | 2022-07-19T08:57:57.000Z | [
"pytorch",
"deberta-v2",
"fill-mask",
"zh",
"transformers",
"bert",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-Deberta-97M-Chinese | 37 | 1 | transformers | 6,677 | ---
language:
- zh
license: apache-2.0
tags:
- bert
inference: true
widget:
- text: "生活的真谛是[MASK]。"
---
# Erlangshen-Deberta-97M-Chinese，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
The 97 million parameter deberta-V2 base model, using 180G Chinese data, 24 A100(40G) training f... |
YYAH/Bert-RU | d9a6d3cbcbfcd190895aaed0c12c1c79c3167c0d | 2022-07-25T15:23:16.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | YYAH | null | YYAH/Bert-RU | 37 | null | transformers | 6,678 | Entry not found |
Frikallo/vgdunkey-vgdunkeybot | 0f3e95368e227f8a905ba9f171154c25fec9ebc7 | 2022-07-29T08:41:49.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | Frikallo | null | Frikallo/vgdunkey-vgdunkeybot | 37 | null | transformers | 6,679 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: vgdunkey-vgdunkeybot
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. -->
# vgdunkey-vgdunkeybot
... |
BritishLibraryLabs/bl-books-genre | b1e0772fb3473db65b0fa6cca03af6817f722b6d | 2022-01-20T14:00:12.000Z | [
"pytorch",
"distilbert",
"text-classification",
"multilingual",
"transformers",
"genre",
"books",
"library",
"historic",
"glam",
"license:mit"
] | text-classification | false | BritishLibraryLabs | null | BritishLibraryLabs/bl-books-genre | 36 | 1 | transformers | 6,680 | ---
language: multilingual
tags:
- genre
- books
- library
- historic
- glam
license: mit
metrics:
- f1
widget:
- text: "Poems on various subjects. Whereto is prefixed a short essay on the structure of English verse"
- text: "Two Centuries of Soho: its institutions, firms, and amusements. By the Clergy of St. Anne's, S... |
Helsinki-NLP/opus-mt-en-az | 5df6d05df97055aea33ee4120019feff558974b8 | 2021-01-18T08:05:00.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"az",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-az | 36 | null | transformers | 6,681 | ---
language:
- en
- az
tags:
- translation
license: apache-2.0
---
### eng-aze
* source group: English
* target group: Azerbaijani
* OPUS readme: [eng-aze](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-aze/README.md)
* model: transformer-align
* source language(s): eng
* target lan... |
Helsinki-NLP/opus-mt-en-mk | d5e09817f85f0b89f81a82d5ae217209d15ce05d | 2021-09-09T21:37:38.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"mk",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-mk | 36 | null | transformers | 6,682 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-mk
* source languages: en
* target languages: mk
* OPUS readme: [en-mk](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-mk/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-en-sem | 7f58a24935a49971fb80ad54ed3fcda545f0035f | 2021-01-18T08:15:41.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"mt",
"ar",
"he",
"ti",
"am",
"sem",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-sem | 36 | null | transformers | 6,683 | ---
language:
- en
- mt
- ar
- he
- ti
- am
- sem
tags:
- translation
license: apache-2.0
---
### eng-sem
* source group: English
* target group: Semitic languages
* OPUS readme: [eng-sem](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-sem/README.md)
* model: transformer
* source lan... |
Helsinki-NLP/opus-mt-eo-de | dc99fd61904de5b6fcf842167c6b5cdee70457a8 | 2021-09-09T21:40:50.000Z | [
"pytorch",
"marian",
"text2text-generation",
"eo",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-eo-de | 36 | null | transformers | 6,684 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-eo-de
* source languages: eo
* target languages: de
* OPUS readme: [eo-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/eo-de/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Nomi97/Chatbot_QA | 5fd705db355abde8649290e2b080c436baff3628 | 2020-07-06T13:38:50.000Z | [
"pytorch",
"longformer",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | Nomi97 | null | Nomi97/Chatbot_QA | 36 | null | transformers | 6,685 | Entry not found |
TransQuest/monotransquest-da-ro_en-wiki | 684be6b6c2523ab2f0763ed06acd74b139f7e36a | 2021-06-03T19:08:40.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ro-en",
"transformers",
"Quality Estimation",
"monotransquest",
"DA",
"license:apache-2.0"
] | text-classification | false | TransQuest | null | TransQuest/monotransquest-da-ro_en-wiki | 36 | null | transformers | 6,686 | ---
language: ro-en
tags:
- Quality Estimation
- monotransquest
- DA
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-accuracy QE t... |
aware-ai/xlmroberta-QA | 04ddaff578c11772b3ac9ec3a97c8aa9a5235e82 | 2020-07-07T10:05:15.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | aware-ai | null | aware-ai/xlmroberta-QA | 36 | 1 | transformers | 6,687 | Entry not found |
alexcleu/wav2vec2-large-xlsr-polish | 3d530ea46d94be16a03b16fca4708a86e6cf7218 | 2021-07-05T19:07:31.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"pl",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | alexcleu | null | alexcleu/wav2vec2-large-xlsr-polish | 36 | null | transformers | 6,688 | ---
language: pl
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2vec2 Large 53 Polish by Alex Leu
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name... |
anirudh21/albert-large-v2-finetuned-mnli | 866c382134ff198ffcda8cd2a8ccdaa4b3b061ba | 2022-02-01T19:12:55.000Z | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"transformers"
] | text-classification | false | anirudh21 | null | anirudh21/albert-large-v2-finetuned-mnli | 36 | null | transformers | 6,689 | Entry not found |
btk/gpt100k | c7d9614154b7a54126e0a8e2759e20e78a2d50f4 | 2021-05-21T14:26:30.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | btk | null | btk/gpt100k | 36 | null | transformers | 6,690 | Entry not found |
butchland/bert-finetuned-ner | 639de575a6990aead9946a027116e8bc166101d2 | 2021-12-17T15:53:25.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | butchland | null | butchland/bert-finetuned-ner | 36 | null | transformers | 6,691 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
cardiffnlp/twitter-roberta-base-sep2020 | 24a573219ff3cd246f022b39dfbc2e29b01e5f4f | 2022-02-09T11:14:34.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-sep2020 | 36 | null | transformers | 6,692 | # Twitter September 2020 (RoBERTa-base, 103M)
This is a RoBERTa-base model trained on 102.86M tweets until the end of September 2020.
More details and performance scores are available in the [TimeLMs paper](https://arxiv.org/abs/2202.03829).
Below, we provide some usage examples using the standard Transformers interf... |
cardiffnlp/twitter-roberta-base-sep2021 | 01e6dc6e35e03bb1d7ea1ff00ecdc6459ce7aec3 | 2022-02-09T11:16:24.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-sep2021 | 36 | null | transformers | 6,693 | # Twitter September 2021 (RoBERTa-base, 120M)
This is a RoBERTa-base model trained on 119.66M tweets until the end of September 2021.
More details and performance scores are available in the [TimeLMs paper](https://arxiv.org/abs/2202.03829).
Below, we provide some usage examples using the standard Transformers interf... |
classla/bcms-bertic-generator | e4e0c2901fac6a67e5710ec893fc9451630fa19b | 2021-05-21T13:29:30.000Z | [
"pytorch",
"electra",
"pretraining",
"hr",
"bs",
"sr",
"cnr",
"hbs",
"transformers",
"masked-lm",
"license:apache-2.0"
] | null | false | classla | null | classla/bcms-bertic-generator | 36 | 1 | transformers | 6,694 | ---
language:
- hr
- bs
- sr
- cnr
- hbs
tags:
- masked-lm
widget:
- text: "Zovem se Marko i radim u [MASK]."
license: apache-2.0
---
# BERTić* [bert-ich] /bɜrtitʃ/ - A transformer language model for Bosnian, Croatian, Montenegrin and Serbian
* The name should resemble the facts (1) that the model was tr... |
facebook/s2t-wav2vec2-large-en-tr | ae0ccd057a5c698ddb7fd439c9238ae49b8865d8 | 2021-11-14T20:39:59.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"en",
"tr",
"dataset:covost2",
"dataset:librispeech_asr",
"arxiv:2104.06678",
"transformers",
"audio",
"speech-translation",
"speech2text2",
"license:mit"
] | automatic-speech-recognition | false | facebook | null | facebook/s2t-wav2vec2-large-en-tr | 36 | 2 | transformers | 6,695 | ---
language:
- en
- tr
datasets:
- covost2
- librispeech_asr
tags:
- audio
- speech-translation
- automatic-speech-recognition
- speech2text2
license: mit
pipeline_tag: automatic-speech-recognition
widget:
- example_title: Common Voice 1
src: https://cdn-media.huggingface.co/speech_samples/common_voice_en_99989.mp3
... |
giacomomiolo/scibert_reupload | e3e95d2b36223eaa73a25de6de157fda8a1a697b | 2021-05-19T17:19:25.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"pretraining",
"transformers"
] | null | false | giacomomiolo | null | giacomomiolo/scibert_reupload | 36 | null | transformers | 6,696 | Entry not found |
google/pegasus-big_patent | a127b8185d15d2ca5eb56198eb31394a2b057abc | 2020-10-22T16:33:21.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/pegasus-big_patent | 36 | 1 | transformers | 6,697 | Entry not found |
huggingtweets/studiocanaluk | fc2ef2798237475275c18e932e98b72ee2e32a99 | 2021-12-10T22:08:55.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/studiocanaluk | 36 | null | transformers | 6,698 | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4... |
jinmang2/textcnn-ko-dialect-classifier | 4972105e9b86a2a0ea1809fe493e46fe8a62d0f6 | 2022-01-01T08:11:25.000Z | [
"pytorch",
"text-classification",
"transformers"
] | text-classification | false | jinmang2 | null | jinmang2/textcnn-ko-dialect-classifier | 36 | null | transformers | 6,699 | Entry not found |
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