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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
naver/efficient-splade-V-large-doc | c4a9877166fbdfafdfc500431fd4bb1b3565e299 | 2022-07-08T11:37:17.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:ms_marco",
"transformers",
"splade",
"query-expansion",
"document-expansion",
"bag-of-words",
"passage-retrieval",
"knowledge-distillation",
"document encoder",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | naver | null | naver/efficient-splade-V-large-doc | 48 | null | transformers | 6,100 | ---
license: cc-by-nc-sa-4.0
language: "en"
tags:
- splade
- query-expansion
- document-expansion
- bag-of-words
- passage-retrieval
- knowledge-distillation
- document encoder
datasets:
- ms_marco
---
## Efficient SPLADE
Efficient SPLADE model for passage retrieval. This architecture uses two distinct models for qu... |
shaina/BNER-BERT | f288e4ec3468c598a13db4b3c35938336bde25a8 | 2022-07-13T23:20:51.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | shaina | null | shaina/BNER-BERT | 48 | null | transformers | 6,101 | ---
inference: false
--- |
bloom-testing/test-bloomd-350m-test-push | cb3edd58d34ec3b1c4581bd1bea43ee54c1a4a99 | 2022-07-15T23:38:06.000Z | [
"pytorch",
"bloom",
"feature-extraction",
"transformers"
] | feature-extraction | false | bloom-testing | null | bloom-testing/test-bloomd-350m-test-push | 48 | null | transformers | 6,102 | Entry not found |
khosseini/bert_1760_1850 | 8be0aec78f070ba612216454c2fe30511f3a9a88 | 2022-07-18T09:27:11.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | khosseini | null | khosseini/bert_1760_1850 | 48 | null | transformers | 6,103 | # Neural Language Models for Nineteenth-Century English: bert_1760_1850
## Introduction
BERT model trained on a large historical dataset of books in English, published between 1760-1850 and comprised of ~1.3 billion tokens.
- Data paper: http://doi.org/10.5334/johd.48
- Github repository: https://github.com/Living-... |
erickdp/gs3n-roberta-model | c138fc92abafacb6a6b705469fe2da06325aea3f | 2022-07-18T16:46:02.000Z | [
"pytorch",
"roberta",
"text-classification",
"es",
"dataset:erixxdp/autotrain-data-gsemodel",
"transformers",
"xerox",
"co2_eq_emissions"
] | text-classification | false | erickdp | null | erickdp/gs3n-roberta-model | 48 | null | transformers | 6,104 | ---
tags: xerox
language: es
widget:
- text: "Debo de levantarme temprano para hacer ejercicio"
datasets:
- erixxdp/autotrain-data-gsemodel
co2_eq_emissions: 0.027846282970913613
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1148842296
- CO2 Emissions (in grams): 0.0278462... |
Creepton/DDLCYuri-DialoGPT-small | 47fff3e8af928c4ee10bdf064db1c106ebee93cb | 2022-07-20T19:17:21.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Creepton | null | Creepton/DDLCYuri-DialoGPT-small | 48 | 1 | transformers | 6,105 | ---
tags:
- conversational
---
# Yuri DialoGPT Model |
lizz27/DialoGPT-small-baymax | e448dd005f9250ba100c79930aec74a90232e7c4 | 2022-07-27T22:11:46.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | lizz27 | null | lizz27/DialoGPT-small-baymax | 48 | null | transformers | 6,106 | ---
tags:
- conversational
---
# Baymax DialoGPT Model |
0x7194633/keyt5-base | 591b9e9121e617461e1a0c8d552109c153610c05 | 2022-01-11T03:52:53.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ru",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | 0x7194633 | null | 0x7194633/keyt5-base | 47 | null | transformers | 6,107 | ---
language:
- ru
license: mit
inference:
parameters:
top_p: 0.9
widget:
- text: "В России может появиться новый штамм коронавируса «омикрон», что может привести к подъему заболеваемости в январе, заявил доцент кафедры инфекционных болезней РУДН Сергей Вознесенский. Он отметил, что вариант «дельта» вызывал больш... |
AriakimTaiyo/DialoGPT-small-Rikka | d15009b1bc06a36b65e4c95a2ecb5621a2941e91 | 2022-02-04T17:37:21.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | AriakimTaiyo | null | AriakimTaiyo/DialoGPT-small-Rikka | 47 | null | transformers | 6,108 | ---
tags:
- conversational
---
# Rikka DialoGPT Model |
BSC-TeMU/roberta-base-bne-capitel-ner-plus | cebd4df6f33dd83209c98ed2fe89e228a59da171 | 2021-10-21T10:29:17.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | BSC-TeMU | null | BSC-TeMU/roberta-base-bne-capitel-ner-plus | 47 | 1 | transformers | 6,109 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "capitel"
- "ner"
datasets:
- "bne"
- "capitel"
metrics:
- "f1"
inference:
parameters:
aggregation_strategy: "first"
---
**⚠️NOTICE⚠️: THIS MODEL HAS BEEN MOVED TO THE FOLLOWING URL AND WILL SOON BE REMOVED:** htt... |
Geotrend/bert-base-ur-cased | d6dd16d492267f862ed86c3e843594f6203ae3d4 | 2021-05-18T20:14:23.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ur",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-ur-cased | 47 | null | transformers | 6,110 | ---
language: ur
datasets: wikipedia
license: apache-2.0
---
# bert-base-ur-cased
We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.
Unlike [distilbert-base-multilingual-cased](https://huggingface.co/disti... |
IlyaGusev/rubert_ext_sum_gazeta | c0718e3691f0400eb215d230ffaf34cb2f42f391 | 2022-07-13T15:35:22.000Z | [
"pytorch",
"bert",
"token-classification",
"ru",
"dataset:IlyaGusev/gazeta",
"transformers",
"summarization",
"t5",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | IlyaGusev | null | IlyaGusev/rubert_ext_sum_gazeta | 47 | null | transformers | 6,111 | ---
language:
- ru
tags:
- summarization
- token-classification
- t5
datasets:
- IlyaGusev/gazeta
license: apache-2.0
inference: false
widget:
- text: "С 1 сентября в России вступают в силу поправки в закон «О банкротстве» — теперь должники смогут освобождаться от непосильных обязательств во внесудебном порядке, если с... |
Langboat/mengzi-oscar-base-retrieval | 84222de18113c7d2806dc9d2bc042aebbaa8c1b4 | 2021-10-14T02:18:16.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"arxiv:2110.06696",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Langboat | null | Langboat/mengzi-oscar-base-retrieval | 47 | 2 | transformers | 6,112 | ---
language:
- zh
license: apache-2.0
---
# Mengzi-oscar-base-retrieval (Chinese Image-text retrieval model)
[Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese](https://arxiv.org/abs/2110.06696)
Mengzi-oscar-base-retrieval is fine-tuned based on Chinese multi-modal pre-training model [Mengz... |
Llamacha/QuBERTa | 0f6c96c475e8ff91eba4bc73719aadf264de444e | 2022-02-07T09:14:51.000Z | [
"pytorch",
"roberta",
"fill-mask",
"qu",
"transformers",
"Llamacha",
"autotrain_compatible"
] | fill-mask | false | Llamacha | null | Llamacha/QuBERTa | 47 | null | transformers | 6,113 | ---
language:
- qu
tags:
- Llamacha
---
# QuBERTa
QuBERTa es un modelo de lenguaje basado en RoBERTa para el quechua. Nuestro modelo de lenguaje fue pre-entrenado con 5M de tokens del quechua sureño (Collao y Chanka).
El modelo utiliza un tokenizador Byte-level BPE con un vocabulario de 52000 tokens de subpalabra... |
Luciano/bert-base-portuguese-cased-finetuned-peticoes | 1b7f9dfb8b17c1e38d4ddade535130d9f60ceb16 | 2022-02-18T10:20:51.000Z | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"pt",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | fill-mask | false | Luciano | null | Luciano/bert-base-portuguese-cased-finetuned-peticoes | 47 | null | transformers | 6,114 | ---
language:
- pt
license: mit
tags:
- generated_from_trainer
model-index:
- name: bert-base-portuguese-cased-finetuned-peticoes
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 t... |
NtDNlp/sentence-embedding-vietnamese | d7500f88bb1558916656dec663644ea3c69a00d0 | 2021-05-27T08:51:12.000Z | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | NtDNlp | null | NtDNlp/sentence-embedding-vietnamese | 47 | null | transformers | 6,115 | #EmbeddingSimilarityEvaluator: Evaluating the model on STS.en-en.txt dataset in epoch 2 after 26000 steps:
| Type | Pearson | Spearman |
| ----------- | ----------- | ----------- |
| Cosine | 0.7650 | 0.8095 |
| Euclidean | 0.8089 | 0.8010 |
| Cosine | 0.8075 | 0.7999 |
| Eucli... |
Rifky/IndoBERT-FakeNews | 792857fe1e032fc18077a80ba67ee4831052b1ee | 2021-09-16T17:54:21.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | Rifky | null | Rifky/IndoBERT-FakeNews | 47 | null | transformers | 6,116 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- null
model-index:
- name: IndoBERT-FakeNews
results:
- task:
name: Text Classification
type: text-classification
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should proba... |
SEBIS/legal_t5_small_summ_en | a78a8c462825accf01c77b6e307d09f47a1d2f45 | 2021-06-23T11:21:55.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"English",
"dataset:jrc-acquis",
"transformers",
"summarization English model",
"autotrain_compatible"
] | text2text-generation | false | SEBIS | null | SEBIS/legal_t5_small_summ_en | 47 | null | transformers | 6,117 |
---
language: English
tags:
- summarization English model
datasets:
- jrc-acquis
widget:
- text: >
THE COMMISSION OF THE EUROPEAN COMMUNITIES, Having regard to the Treaty establishing
the European Community, Having regard to Council Regulation (EC) No 1255/1999 of 17 May 1999
on the common organisatio... |
TransQuest/monotransquest-da-ru_en-reddit_wikiquotes | 8cd7efdbb7b13c7eae9234e6bd3f6a4a8d2ec3cc | 2021-06-03T19:09:24.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ru-en",
"transformers",
"Quality Estimation",
"monotransquest",
"DA",
"license:apache-2.0"
] | text-classification | false | TransQuest | null | TransQuest/monotransquest-da-ru_en-reddit_wikiquotes | 47 | null | transformers | 6,118 | ---
language: ru-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... |
anegi/autonlp-dialogue-summariztion-583416409 | b08fdc8c06f7aacd57b050158b360cd97e280683 | 2022-02-20T06:52:08.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:anegi/autonlp-data-dialogue-summariztion",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | anegi | null | anegi/autonlp-dialogue-summariztion-583416409 | 47 | 1 | transformers | 6,119 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- anegi/autonlp-data-dialogue-summariztion
co2_eq_emissions: 72.26141764997115
---
# Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 583416409
- CO2 Emissions (in grams): 72.26141764997115
## Validation Metrics
- Loss... |
cardiffnlp/bertweet-base-emoji | b9651816c5192d2946a5aa40d61fbe79b9268d2e | 2021-05-20T14:43:48.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | cardiffnlp | null | cardiffnlp/bertweet-base-emoji | 47 | 1 | transformers | 6,120 | |
cardiffnlp/twitter-roberta-base-mar2020 | 30d4b57d6e15351853a4bd693ea25b2720a3175e | 2022-02-09T11:13:09.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-mar2020 | 47 | null | transformers | 6,121 | # Twitter March 2020 (RoBERTa-base, 94M)
This is a RoBERTa-base model trained on 94.46M tweets until the end of March 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 interface. For a... |
deutsche-telekom/mt5-small-sum-de-mit-v1 | c7c12dbe023f38abeeeb598e06013ece248aa6e7 | 2021-08-05T10:17:20.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"de",
"dataset:swiss_text_2019",
"transformers",
"summarization",
"license:mit",
"autotrain_compatible"
] | summarization | false | deutsche-telekom | null | deutsche-telekom/mt5-small-sum-de-mit-v1 | 47 | 2 | transformers | 6,122 | ---
language:
- de
license: mit
tags:
- summarization
datasets:
- swiss_text_2019
---
# mT5-small-sum-de-mit-v1
This is a German summarization model. It is based on the multilingual T5 model [google/mt5-small](https://huggingface.co/google/mt5-small). The special characteristic of this model is that, unlike many ... |
fgaim/tiroberta-pos | 68db11ed771befe4c46e0c3d04f68e4af84d8e7f | 2022-05-14T06:40:08.000Z | [
"pytorch",
"roberta",
"token-classification",
"ti",
"dataset:TLMD",
"dataset:NTC",
"transformers",
"model-index",
"autotrain_compatible"
] | token-classification | false | fgaim | null | fgaim/tiroberta-pos | 47 | 1 | transformers | 6,123 | ---
language: ti
widget:
- text: "ድምጻዊ ኣብርሃም ኣፈወርቂ ንዘልኣለም ህያው ኮይኑ ኣብ ልብና ይነብር"
datasets:
- TLMD
- NTC
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: tiroberta-base-pos
results:
- task:
name: Token Classification
type: token-classification
metrics:
- name: F1
type: f1
... |
huggingtweets/nytimes | cd906983b748414bc7c2a74ceb00c37eee28bbf3 | 2021-10-26T04:52:44.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/nytimes | 47 | null | transformers | 6,124 | ---
language: en
thumbnail: https://www.huggingtweets.com/nytimes/1635223960388/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width:... |
manishiitg/longformer-recruit-qa | 22381ad36f5b2dff159dd03c2793ad5219e6a917 | 2020-11-22T06:49:37.000Z | [
"pytorch",
"longformer",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | manishiitg | null | manishiitg/longformer-recruit-qa | 47 | null | transformers | 6,125 | Entry not found |
maximedb/mfaq-bert | af704097333296e2855a4f908bad2f78d987dc25 | 2021-10-11T08:34:03.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | maximedb | null | maximedb/mfaq-bert | 47 | null | transformers | 6,126 | Entry not found |
meghanabhange/Hinglish-Bert | 601b87008b0a4283bc93be8bc22cccdc77141c25 | 2021-05-19T23:14:48.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | meghanabhange | null | meghanabhange/Hinglish-Bert | 47 | null | transformers | 6,127 | Entry not found |
ml6team/mbart-large-cc25-cnn-dailymail-nl | d04a79b70564b8c825a4682dbb2670845fd16cc1 | 2022-05-16T11:41:37.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"nl",
"dataset:ml6team/cnn_dailymail_nl",
"transformers",
"bart",
"summarization",
"autotrain_compatible"
] | summarization | false | ml6team | null | ml6team/mbart-large-cc25-cnn-dailymail-nl | 47 | 6 | transformers | 6,128 | ---
language:
- nl
tags:
- mbart
- bart
- summarization
datasets:
- ml6team/cnn_dailymail_nl
pipeline_tag: summarization
widget:
- text: 'Het jongetje werd eind april met zwaar letsel naar het ziekenhuis gebracht in Maastricht. Drie weken later overleed het kindje als gevolg van het letsel. Onderzoek moet nog uitwijze... |
mrm8488/camembert-base-finetuned-pawsx-fr | 4d6091ae8d9bbe561994dbe97cf10f8963aec6da | 2021-04-28T15:51:53.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"dataset:xtreme",
"transformers",
"nli"
] | text-classification | false | mrm8488 | null | mrm8488/camembert-base-finetuned-pawsx-fr | 47 | null | transformers | 6,129 | ---
language: fr
datasets:
- xtreme
tags:
- nli
widget:
- text: "La première série a été mieux reçue par la critique que la seconde. La seconde série a été bien accueillie par la critique, mieux que la première."
---
# Camembert-base fine-tuned on PAWS-X-fr for Paraphrase Identification (NLI)
|
qqhann/wav2vec2-large-xlsr-japanese-0325-1200 | 5518a1477809d3523f50d931af7a86057ebda009 | 2021-03-29T10:26:40.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ja",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | qqhann | null | qqhann/wav2vec2-large-xlsr-japanese-0325-1200 | 47 | null | transformers | 6,130 | ---
language: ja
datasets:
- common_voice
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Japanese XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-sp... |
replydotai/albert-xxlarge-v1-finetuned-squad2 | 81ae35092cf89980882fb4f3a3a41a41358ddcd1 | 2020-04-24T16:05:36.000Z | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | replydotai | null | replydotai/albert-xxlarge-v1-finetuned-squad2 | 47 | null | transformers | 6,131 | Entry not found |
ttop324/kogpt2novel | edd5bebf92672e4544c01d153d2a8adc9a5ce771 | 2021-09-23T16:41:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ko",
"transformers",
"license:cc-by-nc-sa-4.0"
] | text-generation | false | ttop324 | null | ttop324/kogpt2novel | 47 | 0 | transformers | 6,132 | ---
language: ko
tags:
- gpt2
license: cc-by-nc-sa-4.0
---
novel finetuned from skt/kogpt2-base-v2 |
uer/chinese_roberta_L-6_H-768 | 126f267ff7e4855d384702d3fea641bfa42b3356 | 2022-07-15T08:13:34.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-6_H-768 | 47 | null | transformers | 6,133 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
usc-isi/sbert-roberta-large-anli-mnli-snli | 922af2f0087b6fae99f3d1705f1aa6495ac7656e | 2021-12-05T21:04:27.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"en",
"dataset:anli",
"dataset:multi_nli",
"dataset:snli",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | usc-isi | null | usc-isi/sbert-roberta-large-anli-mnli-snli | 47 | null | sentence-transformers | 6,134 | ---
language:
- en
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- anli
- multi_nli
- snli
---
# sbert-roberta-large-anli-mnli-snli
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & ... |
w11wo/wav2vec2-xls-r-300m-zh-HK-lm-v2 | 563903f40dcefc6237b7ad93eea93948a6b95f7d | 2022-03-23T18:33:28.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"zh-HK",
"dataset:common_voice",
"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-zh-HK-lm-v2 | 47 | null | transformers | 6,135 | ---
language: zh-HK
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: Wav2Vec2 XLS-R 300M Cantonese (zh-HK) LM
results:
- task:
name: Automatic Speech Recognition
type: automatic-spee... |
yangheng/deberta-v3-large-absa | 9b4cc04cb1bad25805ecb1086081c294388702b5 | 2022-04-22T20:51:51.000Z | [
"pytorch",
"deberta-v2",
"en",
"dataset:laptop14 (w/ augmentation)",
"dataset:restaurant14 (w/ augmentation)",
"dataset:restaurant16 (w/ augmentation)",
"dataset:ACL-Twitter (w/ augmentation)",
"dataset:MAMS (w/ augmentation)",
"dataset:Television (w/ augmentation)",
"dataset:TShirt (w/ augmentati... | null | false | yangheng | null | yangheng/deberta-v3-large-absa | 47 | 1 | transformers | 6,136 | ---
language:
- en
tags:
- aspect-based-sentiment-analysis
- lcf-bert
license: mit
datasets:
- laptop14 (w/ augmentation)
- restaurant14 (w/ augmentation)
- restaurant16 (w/ augmentation)
- ACL-Twitter (w/ augmentation)
- MAMS (w/ augmentation)
- Television (w/ augmentation)
- TShirt (w/ augmentation)
- ... |
edbeeching/decision-transformer-gym-walker2d-medium | da2238c5041fd7fb197d6305f668880454b2f3d4 | 2022-06-29T19:21:47.000Z | [
"pytorch",
"decision_transformer",
"feature-extraction",
"arxiv:2106.01345",
"transformers",
"deep-reinforcement-learning",
"reinforcement-learning",
"decision-transformer",
"gym-continous-control"
] | reinforcement-learning | false | edbeeching | null | edbeeching/decision-transformer-gym-walker2d-medium | 47 | null | transformers | 6,137 | ---
tags:
- deep-reinforcement-learning
- reinforcement-learning
- decision-transformer
- gym-continous-control
pipeline_tag: reinforcement-learning
---
# Decision Transformer model trained on medium trajectories sampled from the Gym Walker2d environment
This is a trained [Decision Transformer](https://arxiv.org/abs/... |
Alvenir/bert-punct-restoration-da | 922d3021a7f7533bb094ea7fba8e26b640586c52 | 2022-03-23T09:05:15.000Z | [
"pytorch",
"bert",
"token-classification",
"da",
"dataset:custom",
"transformers",
"punctuation restoration",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | Alvenir | null | Alvenir/bert-punct-restoration-da | 47 | 1 | transformers | 6,138 | ---
language: da
tags:
- bert
- punctuation restoration
license: apache-2.0
datasets:
- custom
---
# Bert Punctuation Restoration Danish
This model performs the punctuation restoration task in Danish. The method used is sequence classification similar to how NER models
are trained.
## Model description
TODO
### How... |
nielsr/convnext-tiny-finetuned-eurosat | 4f3580e91046d22e9917fd94a2a36e23314e80fd | 2022-04-05T07:25:05.000Z | [
"pytorch",
"convnext",
"image-classification",
"transformers"
] | image-classification | false | nielsr | null | nielsr/convnext-tiny-finetuned-eurosat | 47 | null | transformers | 6,139 | Entry not found |
yhavinga/t5-base-36L-ccmatrix-multi | 27e97747e4680d1569eda7f680391e5cec0586ce | 2022-06-14T10:29:36.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"nl",
"en",
"dataset:yhavinga/mc4_nl_cleaned",
"dataset:yhavinga/ccmatrix",
"transformers",
"translation",
"seq2seq",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | yhavinga | null | yhavinga/t5-base-36L-ccmatrix-multi | 47 | null | transformers | 6,140 | ---
language:
- nl
- en
datasets:
- yhavinga/mc4_nl_cleaned
- yhavinga/ccmatrix
tags:
- t5
- translation
- seq2seq
pipeline_tag: translation
widget:
- text: "It is a painful and tragic spectacle that rises before me: I have drawn back the curtain from the rottenness of man. This word, in my mouth, is at least free fro... |
MEDT/Chatbot_Medium | 782a9bd500243b26d1d12def0cc4e8ff2a6e0c7c | 2022-04-24T15:30:28.000Z | [
"pytorch",
"tf",
"jax",
"rust",
"gpt2",
"text-generation",
"arxiv:1911.00536",
"transformers",
"conversational",
"license:mit"
] | conversational | false | MEDT | null | MEDT/Chatbot_Medium | 47 | null | transformers | 6,141 | ---
thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
tags:
- conversational
license: mit
---
## A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)
DialoGPT is a SOTA large-scale pretrained dialogue response generation model for multiturn conversations.
The [human evaluation... |
alice-hml/mBERT_grammatical_error_tagger | 26ab66e1b2bf6916cb68aba45c66a6b2d556cadb | 2022-05-26T13:30:52.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:other",
"autotrain_compatible"
] | token-classification | false | alice-hml | null | alice-hml/mBERT_grammatical_error_tagger | 47 | null | transformers | 6,142 | ---
license: other
---
|
bigscience-biomedical/bigbio-mtl | aa938e5e1b0e88780212b635baa65f22668fadb3 | 2022-06-05T14:50:03.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | bigscience-biomedical | null | bigscience-biomedical/bigbio-mtl | 47 | null | transformers | 6,143 | Entry not found |
Nonnyss/music-wav2vec2-th-finetune | 098b3684b11cd4184bb40d4d8bde74b86083eb60 | 2022-06-22T07:27:44.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | Nonnyss | null | Nonnyss/music-wav2vec2-th-finetune | 47 | null | transformers | 6,144 | Entry not found |
Taeham/wav2vec2-ksponspeech | 6e79567299694080277a921b108b1600c80e53d2 | 2022-06-21T11:49:09.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Taeham | null | Taeham/wav2vec2-ksponspeech | 47 | null | transformers | 6,145 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-ksponspeech
results: []
---
# wav2vec2-ksponspeech
This model is a fine-tuned version of [Wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results ... |
QCRI/bert-base-cased-chunking | 740e1c79e776d4048aef1eac0954f82cf5d29203 | 2022-06-13T08:31:16.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | token-classification | false | QCRI | null | QCRI/bert-base-cased-chunking | 47 | null | transformers | 6,146 | ---
license: cc-by-nc-4.0
---
|
Yvanzhu/Data-to-text-generation-accelerate | 8c6a6e0fa5ea0ea00abe69c3fe7e68cd3c48106b | 2022-06-19T09:45:09.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Yvanzhu | null | Yvanzhu/Data-to-text-generation-accelerate | 47 | null | transformers | 6,147 | Entry not found |
romainlhardy/bert-finetuned-ner | 1cc035f97e89303e3d5c18d56e78794f981fa19f | 2022-06-26T04:50:31.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | romainlhardy | null | romainlhardy/bert-finetuned-ner | 47 | null | transformers | 6,148 | ---
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... |
turingmachine/hupd-t5-small | c7d01aa85a4603a2cca8c18c914935ee4202ec3f | 2022-07-05T15:28:07.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:HUPD/hupd",
"transformers",
"hupd",
"summarization",
"conditional-generation",
"patents",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | summarization | false | turingmachine | null | turingmachine/hupd-t5-small | 47 | 1 | transformers | 6,149 | ---
language:
- en
tags:
- hupd
- t5
- summarization
- conditional-generation
- patents
license: cc-by-sa-4.0
datasets:
- HUPD/hupd
---
# HUPD T5-Small Summarization Model
This HUPD T5-Small summarization model was fine-tuned on the HUPD dataset. It was originally introduced in [this paper](TBD).
For more inform... |
ClassCat/gpt2-base-french | 902ec822995ce12f979d0a5277ee9c2a1b610df1 | 2022-07-21T09:04:41.000Z | [
"pytorch",
"gpt2",
"text-generation",
"fr",
"dataset:wikipedia",
"dataset:cc100",
"transformers",
"license:cc-by-sa-4.0"
] | text-generation | false | ClassCat | null | ClassCat/gpt2-base-french | 47 | 1 | transformers | 6,150 | ---
language: fr
license: cc-by-sa-4.0
datasets:
- wikipedia
- cc100
widget:
- text: "Je vais à la gare, et"
- text: "J'aime le café, donc"
- text: "Nous avons parlé"
- text: "Je m'appelle"
---
## GPT2 French base model (Uncased)
### Prerequisites
transformers==4.19.2
### Model architecture
This model uses GPT2 ba... |
zhifei/autotrain-chinese-title-summarization-8-1101140174 | acce54c12a959d7100b28d7c4aa02f3655eba931 | 2022-07-07T10:21:29.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"unk",
"dataset:zhifei/autotrain-data-chinese-title-summarization-8",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | zhifei | null | zhifei/autotrain-chinese-title-summarization-8-1101140174 | 47 | null | transformers | 6,151 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- zhifei/autotrain-data-chinese-title-summarization-8
co2_eq_emissions: 1.4118255120710663
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1101140174
- CO2 Emissions (in grams): 1.4118255120710663
## Valid... |
inywer/dumbbot | e54154a54bc2a9d7826e95a0b42aa8a8b97d4819 | 2022-07-11T09:27:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | inywer | null | inywer/dumbbot | 47 | null | transformers | 6,152 | ---
tags:
- conversational
---
# inywer/dumbbot Model |
ai4bharat/IndicBERTv2-alpha | 5c111d6abef5020f3679cd7134a732459597d887 | 2022-07-27T11:21:29.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | ai4bharat | null | ai4bharat/IndicBERTv2-alpha | 47 | null | transformers | 6,153 | IndicBERTv2-alpha
|
Doogie/Waynehills_NLP_muti | 497fef056a730aa629d80f80ec8d1c0327ab3cde | 2022-02-07T00:39:21.000Z | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Doogie | null | Doogie/Waynehills_NLP_muti | 46 | null | transformers | 6,154 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
model-index:
- name: Waynehills_NLP_muti
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. -->
... |
Helsinki-NLP/opus-mt-bg-de | 617ffe639eeeb8c7ee69e0458f43da715b64ac8a | 2021-01-18T07:50:26.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bg",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-bg-de | 46 | null | transformers | 6,155 | ---
language:
- bg
- de
tags:
- translation
license: apache-2.0
---
### bul-deu
* source group: Bulgarian
* target group: German
* OPUS readme: [bul-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-deu/README.md)
* model: transformer
* source language(s): bul
* target language(s):... |
Helsinki-NLP/opus-mt-gem-gem | 92e26534b91b8c1c508e6a556339f252b8551f2b | 2021-01-18T08:52:02.000Z | [
"pytorch",
"marian",
"text2text-generation",
"da",
"sv",
"af",
"nn",
"fy",
"fo",
"de",
"nb",
"nl",
"is",
"en",
"lb",
"yi",
"gem",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-gem-gem | 46 | null | transformers | 6,156 | ---
language:
- da
- sv
- af
- nn
- fy
- fo
- de
- nb
- nl
- is
- en
- lb
- yi
- gem
tags:
- translation
license: apache-2.0
---
### gem-gem
* source group: Germanic languages
* target group: Germanic languages
* OPUS readme: [gem-gem](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gem-gem... |
KoichiYasuoka/bert-large-japanese-luw-upos | 21acbf6d8f4b4c804b1d6b434754447f6bbee113 | 2022-06-27T01:39:54.000Z | [
"pytorch",
"bert",
"token-classification",
"ja",
"dataset:universal_dependencies",
"transformers",
"japanese",
"pos",
"wikipedia",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/bert-large-japanese-luw-upos | 46 | null | transformers | 6,157 | ---
language:
- "ja"
tags:
- "japanese"
- "token-classification"
- "pos"
- "wikipedia"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "国境の長いトンネルを抜けると雪国であった。"
---
# bert-large-japanese-luw-upos
## Model Description
This is a BER... |
NbAiLab/notram-bert-norwegian-cased-080321 | 4a4de1c93d8243866a8c3dd085e05b971b127af1 | 2022-02-06T18:15:16.000Z | [
"pytorch",
"tf",
"bert",
"no",
"transformers",
"norwegian",
"license:cc-by-4.0",
"fill-mask"
] | fill-mask | false | NbAiLab | null | NbAiLab/notram-bert-norwegian-cased-080321 | 46 | null | transformers | 6,158 | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- bert
pipeline_tag: fill-mask
widget:
- text: På biblioteket kan du [MASK] en bok.
- text: Dette er et [MASK] eksempel.
- text: Av og til kan en språkmodell gi et [MASK] resultat.
- text: Som ansat får du [MASK] for at bidrage til borgernes adgang til dansk kultur... |
NikolajMunch/danish-emotion-classification | 17c97ced5466a7f83df22f473662b914d1a00f39 | 2022-01-04T12:14:46.000Z | [
"pytorch",
"bert",
"text-classification",
"da",
"transformers",
"sentiment",
"emotion",
"danish"
] | text-classification | false | NikolajMunch | null | NikolajMunch/danish-emotion-classification | 46 | 1 | transformers | 6,159 | ---
widget:
- text: "Hold da op! Kan det virkelig passe?"
language:
- "da"
tags:
- sentiment
- emotion
- danish
---
# **-- EMODa --**
## BERT-model for danish multi-class classification of emotions
Classifies a danish sentence into one of 6 different emotions:
| Danish emotion | Ekman's emotion |
| -... |
Norod78/distilgpt2-base-pretrained-he | f59d54877b3e45f2fbc603fbad2d83bcc92293ee | 2021-07-26T06:41:24.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"he",
"transformers",
"license:mit"
] | text-generation | false | Norod78 | null | Norod78/distilgpt2-base-pretrained-he | 46 | null | transformers | 6,160 | ---
language: he
thumbnail: https://avatars1.githubusercontent.com/u/3617152?norod.jpg
widget:
- text: "עוד בימי קדם"
- text: "קוראים לי דורון ואני מעוניין ל"
- text: "קוראים לי איציק ואני חושב ש"
- text: "החתול שלך מאוד חמוד ו"
license: mit
---
# hebrew-distilgpt2
A tiny GPT2 based Hebrew text generation model tra... |
Norod78/hewiki-articles-distilGPT2py-il | 88e1aa24acdec518cec7d1573e863b23d9c5393f | 2022-07-04T07:25:03.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"he",
"transformers",
"license:mit"
] | text-generation | false | Norod78 | null | Norod78/hewiki-articles-distilGPT2py-il | 46 | null | transformers | 6,161 | ---
language: he
thumbnail: https://avatars1.githubusercontent.com/u/3617152?norod.jpg
widget:
- text: "<|startoftext|>החוק השני של מועדון קרב הוא"
- text: "<|startoftext|>ראש הממשלה בן גוריון"
- text: "<|startoftext|>למידת מכונה (סרט)"
- text: "<|startoftext|>מנשה פומפרניקל"
- text: "<|startoftext|>אי שוויון "
licen... |
SEBIS/code_trans_t5_small_program_synthese_multitask | 8efc2c60febbe97d36b48bc2adf4833899820028 | 2022-06-02T19:50:32.000Z | [
"pytorch",
"tf",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_small_program_synthese_multitask | 46 | null | transformers | 6,162 | ---
tags:
- summarization
widget:
- text: "you are given an array of numbers a and a number b , compute the difference of elements in a and b"
---
# CodeTrans model for program synthesis
Pretrained model on programming language lisp inspired DSL using the t5 small model architecture. It was first released in
[this r... |
ThomasNLG/t5-qa_webnlg_synth-en | 288c00907a5143ba864272c4bc16b8e98559eebd | 2021-07-09T07:45:27.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:squad_v2",
"arxiv:2104.07555",
"transformers",
"qa",
"question",
"answering",
"SQuAD",
"data2text",
"metric",
"nlg",
"t5-small",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ThomasNLG | null | ThomasNLG/t5-qa_webnlg_synth-en | 46 | null | transformers | 6,163 | ---
language: en
tags:
- qa
- question
- answering
- SQuAD
- data2text
- metric
- nlg
- t5-small
license: mit
datasets:
- squad_v2
model-index:
- name: t5-qa_webnlg_synth-en
results:
- task:
name: Data Question Answering
type: extractive-qa
widget:
- text: "What is the food type at The Eagle? </s> na... |
Yehor/wav2vec2-xls-r-1b-uk-with-news-lm | 1af0c0772402adebe5b373d2ddbc3aab50830c90 | 2022-07-30T07:00:42.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"uk",
"transformers",
"mozilla-foundation/common_voice_7_0",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0"
] | automatic-speech-recognition | false | Yehor | null | Yehor/wav2vec2-xls-r-1b-uk-with-news-lm | 46 | 1 | transformers | 6,164 | ---
language:
- uk
license: cc-by-nc-sa-4.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- uk
xdatasets:
- mozilla-foundation/common_voice_7_0
---
# Ukrainian STT model (with the Big Language Model formed on News Dataset)
🇺🇦 Join Ukrainian Speech Recognition Co... |
allenai/reviews_roberta_base | d446b77ce4028c442841325488a565ce0c2cbd65 | 2021-05-20T13:36:12.000Z | [
"pytorch",
"jax",
"roberta",
"transformers"
] | null | false | allenai | null | allenai/reviews_roberta_base | 46 | null | transformers | 6,165 | Entry not found |
castorini/bpr-nq-question-encoder | bf15a8796a51b290d26552f33b16ab377e5c2d4b | 2021-09-05T00:53:16.000Z | [
"pytorch",
"dpr",
"feature-extraction",
"transformers"
] | feature-extraction | false | castorini | null | castorini/bpr-nq-question-encoder | 46 | null | transformers | 6,166 | This model is converted from the original BPR [repo](https://github.com/studio-ousia/bpr) and fitted into Pyserini:
> Ikuya Yamada, Akari Asai, and Hannaneh Hajishirzi. 2021. Efficient passage retrieval with hashing for open-domain question answering. arXiv:2106.00882. |
danlou/albert-xxlarge-v2-finetuned-csqa | 37eddb04e55c6181d1ab0825bb0078e07f641670 | 2021-07-23T13:55:03.000Z | [
"pytorch",
"albert",
"multiple-choice",
"dataset:commonsense_qa",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | multiple-choice | false | danlou | null | danlou/albert-xxlarge-v2-finetuned-csqa | 46 | 1 | transformers | 6,167 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- commonsense_qa
metrics:
- accuracy
model_index:
- name: albert-xxlarge-v2-finetuned-csqa
results:
- dataset:
name: commonsense_qa
type: commonsense_qa
args: default
metric:
name: Accuracy
type: accuracy
value:... |
diarsabri/LaDPR-context-encoder | e1b5d06963aa4d831908c310e71c73970250e168 | 2021-05-05T21:17:44.000Z | [
"pytorch",
"dpr",
"feature-extraction",
"transformers"
] | feature-extraction | false | diarsabri | null | diarsabri/LaDPR-context-encoder | 46 | null | transformers | 6,168 | Language Model 2
For Language agnostic Dense Passage Retrieval |
edwardgowsmith/pt-finegrained-few-shot | 3b0f2bed8b8393b141e84f58d11907b3faa1a3b0 | 2021-09-08T11:53:56.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | edwardgowsmith | null | edwardgowsmith/pt-finegrained-few-shot | 46 | null | transformers | 6,169 | Entry not found |
google/t5-efficient-base-nl32 | 922119e2e1c0bcef38c8cf3b54c730e25b21f874 | 2022-02-15T10:53:27.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2109.10686",
"transformers",
"deep-narrow",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-efficient-base-nl32 | 46 | 1 | transformers | 6,170 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-BASE-NL32 (Deep-Narrow version)
T5-Efficient-BASE-NL32 is a variation of [Google's original T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) following the [T5 model architectur... |
gsarti/it5-large | d97d1e5ea4b0f789c8bd1cfb2e82b7a55852a500 | 2022-03-09T11:56:08.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:gsarti/clean_mc4_it",
"arxiv:2203.03759",
"transformers",
"seq2seq",
"lm-head",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | gsarti | null | gsarti/it5-large | 46 | null | transformers | 6,171 | ---
language:
- it
datasets:
- gsarti/clean_mc4_it
tags:
- seq2seq
- lm-head
license: apache-2.0
inference: false
thumbnail: https://gsarti.com/publication/it5/featured.png
---
# Italian T5 Large 🇮🇹
The [IT5](https://huggingface.co/models?search=it5) model family represents the first effort in pretraining large-s... |
hfl/chinese-electra-large-generator | 4858952a4b13169d8e0754833d546169900ec845 | 2021-03-03T01:40:52.000Z | [
"pytorch",
"tf",
"electra",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0",
"fill-mask"
] | fill-mask | false | hfl | null | hfl/chinese-electra-large-generator | 46 | null | transformers | 6,172 | ---
language:
- zh
license: "apache-2.0"
pipeline_tag: "fill-mask"
---
**Please use `ElectraForPreTraining` for `discriminator` and `ElectraForMaskedLM` for `generator` if you are re-training these models.**
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has ... |
hfl/cino-small-v2 | 86df088ad499faaa108a0fcd8ba4f33674750139 | 2022-02-21T09:42:05.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"fill-mask",
"zh",
"bo",
"kk",
"ko",
"mn",
"ug",
"yue",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | hfl | null | hfl/cino-small-v2 | 46 | 1 | transformers | 6,173 | ---
language:
- zh
- bo
- kk
- ko
- mn
- ug
- yue
license: "apache-2.0"
---
## CINO: Pre-trained Language Models for Chinese Minority Languages（中国少数民族预训练模型）
Multilingual Pre-trained Language Model, such as mBERT, XLM-R, provide multilingual and cross-lingual ability for language understanding.
We have seen rapid pro... |
huggingartists/taylor-swift | c65013202368a1ace4d1bd2f9a0f5274a6b4ac42 | 2022-07-11T13:52:52.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/taylor-swift",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/taylor-swift | 46 | null | transformers | 6,174 | ---
language: en
datasets:
- huggingartists/taylor-swift
tags:
- huggingartists
- lyrics
- lm-head
- causal-lm
widget:
- text: "I am"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; hei... |
jcblaise/electra-tagalog-base-uncased-discriminator | 82f1d59afc70abf3072cb46eed109dc0f2f397af | 2021-11-12T03:23:51.000Z | [
"pytorch",
"electra",
"pretraining",
"tl",
"transformers",
"tagalog",
"filipino",
"license:gpl-3.0"
] | null | false | jcblaise | null | jcblaise/electra-tagalog-base-uncased-discriminator | 46 | null | transformers | 6,175 | ---
language: tl
tags:
- electra
- tagalog
- filipino
license: gpl-3.0
inference: false
---
**Deprecation Notice**
This model is deprecated. New Filipino Transformer models trained with a much larger corpora are available.
Use [`jcblaise/roberta-tagalog-base`](https://huggingface.co/jcblaise/roberta-tagalog-base) ... |
jkulhanek/augpt-mw-20 | 1b245b111d5554c78b3c82d28bd903b20070df8c | 2021-05-23T05:57:45.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | jkulhanek | null | jkulhanek/augpt-mw-20 | 46 | null | transformers | 6,176 | Entry not found |
megagonlabs/transformers-ud-japanese-electra-base-ginza | 5e3e4cf1fd0c0e5c15f2f1a778484883e7c25bfc | 2021-09-22T09:00:17.000Z | [
"pytorch",
"electra",
"pretraining",
"ja",
"dataset:mC4 Japanese",
"arxiv:1910.10683",
"transformers",
"license:mit"
] | null | false | megagonlabs | null | megagonlabs/transformers-ud-japanese-electra-base-ginza | 46 | 1 | transformers | 6,177 | ---
language: ja
license: mit
datasets:
- mC4 Japanese
---
# transformers-ud-japanese-electra-ginza (sudachitra-wordpiece, mC4 Japanese)
This is an [ELECTRA](https://github.com/google-research/electra) model pretrained on approximately 200M Japanese sentences extracted from the [mC4](https://huggingface.co/datasets/m... |
pdelobelle/robBERT-base | b4336a12103e60b43e0737167355f603ed5e2666 | 2021-05-20T19:16:19.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | pdelobelle | null | pdelobelle/robBERT-base | 46 | null | transformers | 6,178 | Entry not found |
pucpr/bioBERTpt-squad-v1.1-portuguese | 972918d7b7b6ed71a752276a30d71f7e9654471a | 2021-05-20T03:08:26.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"question-answering",
"pt",
"transformers",
"bioBERTpt",
"autotrain_compatible"
] | question-answering | false | pucpr | null | pucpr/bioBERTpt-squad-v1.1-portuguese | 46 | 5 | transformers | 6,179 | ---
language: pt
tags:
- question-answering
- bert
- bioBERTpt
- pytorch
metrics:
- squad
widget:
- text: "O que é AVC?"
context: "O AVC (Acidente vascular cerebral) é a segunda principal causa de morte no Brasil e a principal causa de incapacidade em adultos, retirando do mercado de trabalho milhares de brasileiros.... |
shahukareem/wav2vec2-large-xlsr-53-dhivehi | 4a8b27a97dd143558a0feaa6164228ac708a7da3 | 2021-03-28T08:47:31.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"dv",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | shahukareem | null | shahukareem/wav2vec2-large-xlsr-53-dhivehi | 46 | null | transformers | 6,180 | ---
language: dv
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Shahu Kareem XLSR Wav2Vec2 Large 53 Dhivehi
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
tsdocode/text-to-sql | 1c92c784b2c568e9eb9915ffbdb1d3a15e066738 | 2021-09-03T06:21:03.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | tsdocode | null | tsdocode/text-to-sql | 46 | 1 | transformers | 6,181 | Simple text to SQL |
biu-nlp/contextualizer_qasrl | 8062db2421fe9d8358be48b8c13349fef335622b | 2022-04-13T20:41:47.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | biu-nlp | null | biu-nlp/contextualizer_qasrl | 46 | null | transformers | 6,182 | ---
license: mit
---
|
CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_42 | dccb43de740f58cace45dee142dc20575349ad16 | 2022-05-10T23:20:25.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | CEBaB | null | CEBaB/lstm.CEBaB.sa.2-class.exclusive.seed_42 | 46 | null | transformers | 6,183 | Entry not found |
sanjay-m1/informal-to-formal | d7abd7b10df02aaad7fce872942c93bf1b92debc | 2022-05-21T16:57:38.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sanjay-m1 | null | sanjay-m1/informal-to-formal | 46 | null | transformers | 6,184 | ## This model belongs to the Styleformer project
[Please refer to github page](https://github.com/PrithivirajDamodaran/Styleformer)
|
deepparag/Aeona-Beta | 94f894e68388ad7db9cfb43a489ab6132892bc1f | 2022-07-26T00:23:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:mit"
] | conversational | false | deepparag | null | deepparag/Aeona-Beta | 46 | 1 | transformers | 6,185 | ---
thumbnail: https://images-ext-2.discordapp.net/external/Wvtx1L98EbA7DR2lpZPbDxDuO4qmKt03nZygATZtXgk/%3Fsize%3D4096/https/cdn.discordapp.com/avatars/931226824753700934/338a9e413bbceaeb9095a29e97d4fac0.png
tags:
- conversational
license: mit
---
# Aeona | Chatbot
![Aeona Banner](https://github.com/deepsarda/Aeona/bl... |
mgonnav/finetuning-pysentimiento-war-tweets | db4407ee635fd9a249ea7332c00fa602e91c0610 | 2022-07-11T03:33:41.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | mgonnav | null | mgonnav/finetuning-pysentimiento-war-tweets | 46 | null | transformers | 6,186 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-pysentimiento-war-tweets
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. -... |
IlyaGusev/ru-word-stress-transformer | ce030218eac4c63a98aa4a7e1f6250279a686e24 | 2022-07-13T15:34:21.000Z | [
"pytorch",
"deberta-v2",
"token-classification",
"ru",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | IlyaGusev | null | IlyaGusev/ru-word-stress-transformer | 46 | null | transformers | 6,187 | ---
language:
- ru
tags:
- token-classification
license: apache-2.0
inference: false
---
# RuWordStressTransformer
## Model description
Transformer encoder for predicting word stress in Russian.
## Intended uses & limitations
#### How to use
```python
from transformers import AutoTokenizer, AutoModelForTokenCla... |
duchung17/wav2vec2-base-vivos | 42688d1be97d5fd67f2b823ae0ea1d45213dc43c | 2022-07-12T08:19:27.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | duchung17 | null | duchung17/wav2vec2-base-vivos | 46 | null | transformers | 6,188 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-vivos
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. -->
# wav2vec2-base-v... |
Billwzl/20split_dataset | 5e544b6dfb1a29cc09ca803790c365cf513d4978 | 2022-07-14T03:21:48.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | Billwzl | null | Billwzl/20split_dataset | 46 | 1 | transformers | 6,189 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: 20split_dataset
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. -->
# 20split_dataset
Th... |
NAACL2022/spider-trivia-ctx-encoder | 535fe181313ccc8ed9e24071886b00f89e3f00a3 | 2022-07-09T19:19:59.000Z | [
"pytorch",
"dpr",
"arxiv:2112.07708",
"transformers"
] | null | false | NAACL2022 | null | NAACL2022/spider-trivia-ctx-encoder | 46 | 4 | transformers | 6,190 | # Spider-TriviaQA: Context Encoder
This is the context encoder of the model fine-tuned on TriviaQA (and initialized from Spider) discussed in our paper [Learning to Retrieve Passages without Supervision](https://arxiv.org/abs/2112.07708).
## Usage
We used weight sharing for the query encoder and passage encoder, so ... |
DHBaek/gpt2-stackoverflow-question-contents-generator | 455d4f2115745affb720ad973f13a72413d8d668 | 2021-06-15T02:18:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | DHBaek | null | DHBaek/gpt2-stackoverflow-question-contents-generator | 45 | null | transformers | 6,191 | Entry not found |
Helsinki-NLP/opus-mt-pt-uk | 911074b88a1092b3d0a7dff4d8d02ee5571127d2 | 2020-08-21T14:42:48.000Z | [
"pytorch",
"marian",
"text2text-generation",
"pt",
"uk",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-pt-uk | 45 | null | transformers | 6,192 | ---
language:
- pt
- uk
tags:
- translation
license: apache-2.0
---
### por-ukr
* source group: Portuguese
* target group: Ukrainian
* OPUS readme: [por-ukr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/por-ukr/README.md)
* model: transformer-align
* source language(s): por
* target la... |
LegolasTheElf/Wav2Vec2_XLSR_Bengali_V3 | 8a21e35a22df68e076f974b5067c1af3a241a858 | 2022-01-26T14:29:33.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | LegolasTheElf | null | LegolasTheElf/Wav2Vec2_XLSR_Bengali_V3 | 45 | null | transformers | 6,193 | Entry not found |
MoritzLaurer/covid-policy-roberta-21 | 0ebcdb512ccb44e3b3a4c4e30168b7d59cf1309e | 2021-05-20T12:11:07.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"en",
"transformers"
] | text-classification | false | MoritzLaurer | null | MoritzLaurer/covid-policy-roberta-21 | 45 | 1 | transformers | 6,194 | ---
language:
- en
tags:
- text-classification
metrics:
- accuracy (balanced)
- F1 (weighted)
widget:
- text: "All non-essential work activity will stop in Spain from tomorrow until 9 April but there is some confusion as to which jobs can continue under the new lockdown restrictions"
---
# Covid-Policy-RoBERTa-21
Thi... |
ReynaQuita/twitter_disaster_bert_large | 43d82dca4c9ac69682c359530978652c4ade4908 | 2021-11-01T08:03:58.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | ReynaQuita | null | ReynaQuita/twitter_disaster_bert_large | 45 | null | transformers | 6,195 | Entry not found |
SetFit/deberta-v3-large__sst2__train-16-8 | d47e833d4ad44464e2aa0be2208d4793beed093f | 2022-02-10T11:15:56.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | SetFit | null | SetFit/deberta-v3-large__sst2__train-16-8 | 45 | null | transformers | 6,196 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large__sst2__train-16-8
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 com... |
anindabitm/sagemaker-BioclinicalBERT-ADR | 98e337743a736257aedadf210f293104cfeb4d82 | 2021-11-18T19:24:42.000Z | [
"pytorch",
"bert",
"question-answering",
"dataset:ade_corpus_v2",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | anindabitm | null | anindabitm/sagemaker-BioclinicalBERT-ADR | 45 | null | transformers | 6,197 | ---
tags:
- generated_from_trainer
datasets:
- ade_corpus_v2
model-index:
- name: sagemaker-BioclinicalBERT-ADR
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. -->
#... |
benjamin/gpt2-wechsel-french | 81aa3fe79c2b6b714b1fc460b4d9609153338847 | 2022-07-13T23:44:12.000Z | [
"pytorch",
"gpt2",
"text-generation",
"fr",
"transformers",
"license:mit"
] | text-generation | false | benjamin | null | benjamin/gpt2-wechsel-french | 45 | null | transformers | 6,198 | ---
language: fr
license: mit
---
# gpt2-wechsel-french
Model trained with WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
See the code here: https://github.com/CPJKU/wechsel
And the paper here: https://aclanthology.org/2022.naacl-main.293/
## Perf... |
browndw/docusco-bert | 1cd3532231d21577c5cb1bc14f0a991d6f803717 | 2022-07-22T22:10:46.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"en",
"dataset:COCA",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible"
] | token-classification | false | browndw | null | browndw/docusco-bert | 45 | null | transformers | 6,199 | ---
language: en
datasets: COCA
---
# docusco-bert
## Model description
**docusco-bert** is a fine-tuned BERT model that is ready to use for **token classification**. The model was trained on data sampled from the Corpus of Contemporary American English ([COCA](https://www.english-corpora.org/coca/)) and classifies t... |
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