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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jorgeutd/albert-base-v2-finetuned-ner | bd60314074adfe7774c54005412b841bd1fbf85c | 2022-07-13T14:01:57.000Z | [
"pytorch",
"albert",
"token-classification",
"en",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Jorgeutd | null | Jorgeutd/albert-base-v2-finetuned-ner | 20 | null | transformers | 8,300 | ---
license: apache-2.0
tags:
- generated_from_trainer
language: en
widget:
- text: "My name is Scott and I live in Columbus."
- text: "Apple was founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne."
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: albert-base-v2-finetu... |
KBLab/bert-base-swedish-cased-alpha | a43ddce87d17e237b3faff5597cc5b11a0204dbb | 2021-05-18T21:17:41.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | KBLab | null | KBLab/bert-base-swedish-cased-alpha | 20 | null | transformers | 8,301 | Entry not found |
Lowin/chinese-bigbird-small-1024 | 381bda828e7537e47f4201e98d7a2c793927b1f5 | 2021-11-24T16:07:28.000Z | [
"pytorch",
"big_bird",
"feature-extraction",
"zh",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | Lowin | null | Lowin/chinese-bigbird-small-1024 | 20 | 2 | transformers | 8,302 | ---
language:
- zh
license:
- apache-2.0
---
```python
import jieba_fast
from transformers import BertTokenizer
from transformers import BigBirdModel
class JiebaTokenizer(BertTokenizer):
def __init__(
self, pre_tokenizer=lambda x: jieba_fast.cut(x, HMM=False), *args, **kwargs
):
super().__init__... |
NYTK/text-generation-news-gpt2-small-hungarian | 6afd6d03dff79cecfe8f7434e656fbb59601ba68 | 2022-02-14T13:34:08.000Z | [
"pytorch",
"gpt2",
"text-generation",
"hu",
"transformers",
"license:gpl"
] | text-generation | false | NYTK | null | NYTK/text-generation-news-gpt2-small-hungarian | 20 | 1 | transformers | 8,303 | ---
language:
- hu
tags:
- text-generation
license: gpl
widget:
- text: "Szeptember végén zárul a balatoni szezon"
---
# Hungarian GPT-2 new generator
For further models, scripts and details, see [our repository](https://github.com/nytud/neural-models) or [our demo site](https://juniper.nytud.hu/demo/nlp).
- Pre... |
NbAiLab/notram-bert-norwegian-uncased-080321 | 1fefec3d02a2382b3fbfa1bac01a29310b95dce8 | 2021-12-02T12:50:54.000Z | [
"pytorch",
"tf",
"bert",
"no",
"transformers",
"norwegian",
"license:cc-by-4.0",
"fill-mask"
] | fill-mask | false | NbAiLab | null | NbAiLab/notram-bert-norwegian-uncased-080321 | 20 | null | transformers | 8,304 | ---
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... |
Nenma/romanian-bert-fake-news | 08e2b727f3ba163a0368f66b01b2f208fa153493 | 2021-05-18T20:28:44.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Nenma | null | Nenma/romanian-bert-fake-news | 20 | null | transformers | 8,305 | Entry not found |
RavenK/bert-base-uncased-sst2 | 1dc5c372f1c2b1183775cb0af5856d2455fd7d19 | 2021-07-18T12:34:51.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | RavenK | null | RavenK/bert-base-uncased-sst2 | 20 | null | transformers | 8,306 | Entry not found |
RecordedFuture/Swedish-Sentiment-Fear-Targets | 49874d4ba02438ba4a488fcdbd7a1d5e4c60ecb8 | 2021-05-24T12:47:21.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"sv",
"transformers",
"license:mit",
"autotrain_compatible"
] | token-classification | false | RecordedFuture | null | RecordedFuture/Swedish-Sentiment-Fear-Targets | 20 | null | transformers | 8,307 | ---
language: sv
license: mit
---
## Swedish BERT models for sentiment analysis, Sentiment targets.
[Recorded Future](https://www.recordedfuture.com/) together with [AI Sweden](https://www.ai.se/en) releases two language models for target/role assignment in Swedish. The two models are based on the [KB/bert-base-swedi... |
Rubens/Wav2Vec2-Large-XLSR-53-a-Portuguese | 27fe34c2d0f959644eb3db8a25ce9b498de9b4bb | 2021-07-05T17:16:42.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"apache-2.0",
"portuguese-speech-corpus",
"xlsr-fine-tuning-week",
"PyTorch",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Rubens | null | Rubens/Wav2Vec2-Large-XLSR-53-a-Portuguese | 20 | null | transformers | 8,308 | ---
language: pt
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- speech
- wav2vec2
- pt
- apache-2.0
- portuguese-speech-corpus
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
- PyTorch
license: apache-2.0
model-index:
- name: Rubens XLSR Wav2Vec2 Large 53 Portuguese
results:
- task:
... |
SEBIS/code_trans_t5_base_code_documentation_generation_javascript | b9dd33537a9493141142f932f11484ad14f91040 | 2021-06-23T04:28:07.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_base_code_documentation_generation_javascript | 20 | null | transformers | 8,309 | ---
tags:
- summarization
widget:
- text: "function isStandardBrowserEnv ( ) { if ( typeof navigator !== 'undefined' && ( navigator . product === 'ReactNative' || navigator . product === 'NativeScript' || navigator . product === 'NS' ) ) { return false ; } return ( typeof window !== 'undefined' && typeof document !== '... |
SEBIS/code_trans_t5_base_source_code_summarization_python_multitask_finetune | e6d2f1b759be8d9a0edaa69c6f4cc102ed9ffc0f | 2021-06-23T05:23:42.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_base_source_code_summarization_python_multitask_finetune | 20 | null | transformers | 8,310 | ---
tags:
- summarization
widget:
- text: '''with open ( CODE_STRING , CODE_STRING ) as in_file : buf = in_file . readlines ( ) with open ( CODE_STRING , CODE_STRING ) as out_file : for line in buf : if line == " ; Include this text " : line = line + " Include below " out_file . w... |
SEBIS/code_trans_t5_large_code_comment_generation_java_multitask_finetune | a931d6373d6118a0ec8206166c683021dbdd5067 | 2021-06-23T06:03:04.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_code_comment_generation_java_multitask_finetune | 20 | null | transformers | 8,311 | ---
tags:
- summarization
widget:
- text: "protected String renderUri ( URI uri ) { return uri . toASCIIString ( ) ; }"
---
# CodeTrans model for code documentation generation java
Pretrained model on programming language java using the t5 large model architecture. It was first released in
[this repository](https://... |
SEBIS/code_trans_t5_small_code_documentation_generation_java_transfer_learning_finetune | 7bf37407a4befd6eb741e7b057f28b66c47e423c | 2021-06-23T10:02:12.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_small_code_documentation_generation_java_transfer_learning_finetune | 20 | null | transformers | 8,312 | ---
tags:
- summarization
widget:
- text: "public static < T , U > Function < T , U > castFunction ( Class < U > target ) { return new CastToClass < T , U > ( target ) ; }"
---
# CodeTrans model for code documentation generation java
Pretrained model on programming language java using the t5 small model architectur... |
SEBIS/legal_t5_small_trans_en_it | f36c868c0d29f5bcfae7a31dcccffb2688bef68c | 2021-06-23T09:38:31.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"English Italian",
"dataset:dcep europarl jrc-acquis",
"transformers",
"translation English Italian model",
"autotrain_compatible"
] | text2text-generation | false | SEBIS | null | SEBIS/legal_t5_small_trans_en_it | 20 | null | transformers | 8,313 |
---
language: English Italian
tags:
- translation English Italian model
datasets:
- dcep europarl jrc-acquis
widget:
- text: "Answer given by Mrs Benita Ferrero-Waldner on behalf of the Commission"
---
# legal_t5_small_trans_en_it model
Model on translating legal text from English to Italian. It was first releas... |
Shahm/t5-small-german | 1aad8196c5c36006e7020ba3d70fc4dd3df77630 | 2021-12-25T21:28:47.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"dataset:mlsum",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Shahm | null | Shahm/t5-small-german | 20 | null | transformers | 8,314 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: t5-seven-epoch-base-german
results:
- task:
name: Summarization
type: summarization
dataset:
name: mlsum de
type: mlsum
args: de
metrics:
- name: Rouge1
type... |
Supiri/t5-base-conversation | ba7d7a10bdce0da458082c9bd6c9ba36608e2ee3 | 2022-01-18T17:56:42.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"en",
"dataset:cornell_movie_dialog",
"transformers",
"NLP",
"ChatBot",
"Game AI",
"license:gpl-3.0",
"autotrain_compatible"
] | text2text-generation | false | Supiri | null | Supiri/t5-base-conversation | 20 | 1 | transformers | 8,315 | ---
language: en
datasets:
- cornell_movie_dialog
license: gpl-3.0
tags:
- NLP
- ChatBot
- Game AI
metrics:
- rouge
widget:
- text: "personality: Hinata was soft-spoken and polite, always addressing people with proper honorifics. She is kind, always thinking of others more than for herself, caring for their fee... |
TransQuest/monotransquest-da-si_en-wiki | 1f5301636621e0d920e35df7f7084f7fcee97ee1 | 2021-06-03T19:10:02.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"si-en",
"transformers",
"Quality Estimation",
"monotransquest",
"DA",
"license:apache-2.0"
] | text-classification | false | TransQuest | null | TransQuest/monotransquest-da-si_en-wiki | 20 | null | transformers | 8,316 | ---
language: si-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... |
ZYW/en-de-vi-zh-es-model | 320566961cfc73fa62074c9f913ecab4128f3c6c | 2021-05-29T17:33:12.000Z | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"model-index",
"autotrain_compatible"
] | question-answering | false | ZYW | null | ZYW/en-de-vi-zh-es-model | 20 | null | transformers | 8,317 | ---
model-index:
- name: en-de-vi-zh-es-model
---
<!-- 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. -->
# en-de-vi-zh-es-model
This model was trained from scratch on an unkown dataset... |
abhishek/autonlp-prodigy-10-3362554 | f0cd009bfbce1ba2e374b0fee01ae5f554a80714 | 2021-12-20T11:11:03.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"dataset:abhishek/autonlp-data-prodigy-10",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | token-classification | false | abhishek | null | abhishek/autonlp-prodigy-10-3362554 | 20 | 1 | transformers | 8,318 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- abhishek/autonlp-data-prodigy-10
co2_eq_emissions: 5.340540212393564
---
# Model Trained Using AutoNLP
- Problem type: Entity Extraction
- Model ID: 3362554
- CO2 Emissions (in grams): 5.340540212393564
## Validation Metrics
- Loss: 0.14... |
aditeyabaral/sentencetransformer-indic-bert | bad302e8800d138908d02c2b3db4d27d2a2c56b7 | 2021-10-28T02:17:50.000Z | [
"pytorch",
"albert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | aditeyabaral | null | aditeyabaral/sentencetransformer-indic-bert | 20 | null | sentence-transformers | 8,319 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# aditeyabaral/sentencetransformer-indic-bert
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can... |
airKlizz/bert2bert-multi-fr-wiki-news | 44d0303ffac4a9c514ad8b8149ed1209ee00ff1d | 2021-10-17T20:10:30.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"fr",
"transformers",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | airKlizz | null | airKlizz/bert2bert-multi-fr-wiki-news | 20 | null | transformers | 8,320 | ---
language: fr
license: mit
---
|
akdeniz27/bert-turkish-text-classification | cc43a667ab6ada0a6322d04b2b373073c352f8c1 | 2021-09-10T11:43:28.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"tr",
"transformers"
] | text-classification | false | akdeniz27 | null | akdeniz27/bert-turkish-text-classification | 20 | null | transformers | 8,321 | ---
language: tr
---
# Turkish Text Classification for Complaints Data Set
This model is a fine-tune model of https://github.com/stefan-it/turkish-bert by using text classification data with 9 categories as follows:
id_to_category = {0: 'KONFORSUZLUK', 1: 'TARİFE İHLALİ', 2: 'DURAKTA DURMAMA', 3: 'ŞOFÖR-PERSONEL ŞİK... |
alistvt/bert-base-uncased-pretrained-clm-coqa-stories | 933ed9493c2e10454c8485effdf8d8c81c6a60d5 | 2022-01-21T12:36:10.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | alistvt | null | alistvt/bert-base-uncased-pretrained-clm-coqa-stories | 20 | null | transformers | 8,322 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-pretrained-clm-coqa-stories
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comme... |
alon-albalak/xlm-roberta-base-xquad | 309f3157de9312876bcd0d893af373c6fabec648 | 2021-11-05T20:24:39.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"dataset:xquad",
"transformers",
"multilingual",
"autotrain_compatible"
] | question-answering | false | alon-albalak | null | alon-albalak/xlm-roberta-base-xquad | 20 | 1 | transformers | 8,323 | ---
tags:
- multilingual
datasets:
- xquad
---
# xlm-roberta-base for multilingual QA
# Overview
**Language Model**: xlm-roberta-base \
**Downstream task**: Extractive QA \
**Training data**: [XQuAD](https://github.com/deepmind/xquad)\
**Testing Data**: [XQuAD](https://github.com/deepmind/xquad)
# Hyperparameters
```p... |
ami-wav2vec2/wav2vec2-large-lv60-ami_multi-tune_dropout_0.0001_16 | 78da7a507b8fafc8ecb68c27a0e867d5ffe7bcb6 | 2021-11-25T05:52:03.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"en",
"transformers",
"ami",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | ami-wav2vec2 | null | ami-wav2vec2/wav2vec2-large-lv60-ami_multi-tune_dropout_0.0001_16 | 20 | null | transformers | 8,324 | ---
language:
- en
license: apache-2.0
tags:
- automatic-speech-recognition
- ami
- generated_from_trainer
model-index:
- name: wav2vec2-large-lv60-ami_multi-tune_dropout_0.0001_16
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should... |
anton-l/sew-d-mid-400k-ft-keyword-spotting | e101f125b71e56cf53cf1ffc1c9ae51cfeafa83c | 2022-01-26T14:47:43.000Z | [
"pytorch",
"tensorboard",
"sew-d",
"audio-classification",
"transformers"
] | audio-classification | false | anton-l | null | anton-l/sew-d-mid-400k-ft-keyword-spotting | 20 | null | transformers | 8,325 | Entry not found |
cambridgeltl/tacl-bert-base-uncased | 7a33c68a2dfc3f90151674f06be0f0decb1eb9f2 | 2021-10-28T17:50:49.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/tacl-bert-base-uncased | 20 | null | transformers | 8,326 | Entry not found |
cardiffnlp/bertweet-base-stance-climate | cedb52e8dd52bb0ee061cebe893087e062ad6aef | 2021-05-20T14:54:22.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | cardiffnlp | null | cardiffnlp/bertweet-base-stance-climate | 20 | null | transformers | 8,327 | |
chinhon/bart-large-cnn-summarizer_03 | 4952d1523e24ae0932d9704d7129e7bb62eb095b | 2021-11-08T04:29:43.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | chinhon | null | chinhon/bart-large-cnn-summarizer_03 | 20 | null | transformers | 8,328 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-summarizer_03
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. -->... |
chinhon/headline_writer2 | 75eb858756c63923603144bd5b3c00c493071697 | 2021-10-24T20:54:50.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:chinhon/autonlp-data-sg_headline_generator",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | chinhon | null | chinhon/headline_writer2 | 20 | null | transformers | 8,329 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- chinhon/autonlp-data-sg_headline_generator
co2_eq_emissions: 396.629376395644
---
# Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 25965856
- CO2 Emissions (in grams): 396.629376395644
## Validation Metrics
- Loss:... |
danlou/roberta-large-finetuned-csqa | dadcd61b4ecc12bcdf66d34327dfa4960d575087 | 2021-07-23T14:15:11.000Z | [
"pytorch",
"roberta",
"multiple-choice",
"dataset:commonsense_qa",
"transformers",
"generated_from_trainer",
"license:mit"
] | multiple-choice | false | danlou | null | danlou/roberta-large-finetuned-csqa | 20 | null | transformers | 8,330 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- commonsense_qa
metrics:
- accuracy
model_index:
- name: roberta-large-finetuned-csqa
results:
- dataset:
name: commonsense_qa
type: commonsense_qa
args: default
metric:
name: Accuracy
type: accuracy
value: 0.73300576... |
dbmdz/bert-small-historic-multilingual-cased | 0cf6b98b9e7967668461bbfb93b2133ab508bf4d | 2021-12-06T14:30:02.000Z | [
"pytorch",
"tf",
"tensorboard",
"bert",
"fill-mask",
"multilingual",
"arxiv:1908.08962",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/bert-small-historic-multilingual-cased | 20 | null | transformers | 8,331 | ---
language: multilingual
license: mit
widget:
- text: "and I cannot conceive the reafon why [MASK] hath"
- text: "Täkäläinen sanomalehdistö [MASK] erit - täin"
- text: "Det vore [MASK] häller nödvändigt att be"
- text: "Comme, à cette époque [MASK] était celle de la"
- text: "In [MASK] an atmosphärischen Nahrungsmitt... |
dvilares/bertinho-gl-base-cased | fff68078ef30430ef266e0d21237d395a2afadab | 2021-05-19T16:17:47.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"gl",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dvilares | null | dvilares/bertinho-gl-base-cased | 20 | 2 | transformers | 8,332 | ---
language: gl
widget:
- text: "As filloas son un [MASK] típico do entroido en Galicia "
---
# Bertinho-gl-base-cased
A pre-trained BERT model for Galician (12layers, cased). Trained on Wikipedia
|
e-tony/gpt2-rnm | e13bc88a5df0d22e2d27498ed625cfd9396b41d5 | 2021-05-21T15:43:11.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | e-tony | null | e-tony/gpt2-rnm | 20 | null | transformers | 8,333 | ### How to use
You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we
set a seed for reproducibility:
```python
>>> from transformers import pipeline, set_seed
>>> generator = pipeline('text-generation', model='e-tony/gpt2-rnm')
>>> set_seed(42)
>>> gen... |
ethzhou/newJooby | 2688bc4d063f291ec98a9c214081ab1d47dbee7f | 2021-09-17T07:09:09.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | ethzhou | null | ethzhou/newJooby | 20 | null | transformers | 8,334 | ---
tags:
- conversational
---
#blabla |
facebook/wav2vec2-large-es-voxpopuli | 6e206dcc5ee8627f4fbb73869b36acc023943b52 | 2021-07-06T02:07:04.000Z | [
"pytorch",
"jax",
"wav2vec2",
"pretraining",
"es",
"arxiv:2101.00390",
"transformers",
"audio",
"automatic-speech-recognition",
"voxpopuli",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-large-es-voxpopuli | 20 | null | transformers | 8,335 | ---
language: es
tags:
- audio
- automatic-speech-recognition
- voxpopuli
license: cc-by-nc-4.0
---
# Wav2Vec2-Large-VoxPopuli
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) large model pretrained on the es unlabeled subset of [VoxPopuli corpus](https:/... |
flax-community/Sinhala-roberta | c4fa46aceabf09f35525f45e5eaf3096e7bf6c01 | 2021-07-17T03:27:17.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"feature-extraction",
"si",
"transformers",
"fill-mask",
"sinhala"
] | feature-extraction | false | flax-community | null | flax-community/Sinhala-roberta | 20 | null | transformers | 8,336 | ---
language: si
tags:
- fill-mask
- sinhala
- roberta
---
## Sinhala Roberta model trained on MC4 Sinhala dataset (manually cleaned) |
gealexandri/greeksocialbert-base-greek-uncased-v1 | 909ea4dd991186fc8a66688ef543666606aeb67d | 2021-10-14T13:50:30.000Z | [
"pytorch",
"tf",
"bert",
"fill-mask",
"el",
"transformers",
"autotrain_compatible"
] | fill-mask | false | gealexandri | null | gealexandri/greeksocialbert-base-greek-uncased-v1 | 20 | null | transformers | 8,337 | ---
language: el
---
# GreekSocialBERT
## Model description
A Greek language model based on [GreekBERT](https://huggingface.co/nlpaueb/bert-base-greek-uncased-v1)
## Training data
The training data is a corpus of 458,293 documents collected from Greek social media accounts.
The training corpus has been collected... |
gerardozq/biobert_v1.1_pubmed-finetuned-squad | b8626ebbc832c8068be59d0e5f67443de46e4cb5 | 2021-11-11T16:26:29.000Z | [
"pytorch",
"tensorboard",
"bert",
"question-answering",
"dataset:squad_v2",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | gerardozq | null | gerardozq/biobert_v1.1_pubmed-finetuned-squad | 20 | null | transformers | 8,338 | ---
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: biobert_v1.1_pubmed-finetuned-squad
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. -->
... |
google/fnet-large | 7753dcad10e795fee9b01a64987933d9ff2b0963 | 2021-09-29T12:50:43.000Z | [
"pytorch",
"fnet",
"pretraining",
"en",
"dataset:c4",
"arxiv:2105.03824",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/fnet-large | 20 | 2 | transformers | 8,339 | ---
language: en
tags:
- fnet
license: apache-2.0
datasets:
- c4
---
# FNet large model
Pretrained model on English language using a masked language modeling (MLM) and next sentence prediction (NSP) objective. It was
introduced in [this paper](https://arxiv.org/abs/2105.03824) and first released in [this repository]... |
google/t5-efficient-base-nl36 | bb0086c0a3cda226da13e718da9700b2ee5e6b73 | 2022-02-15T10:53:30.000Z | [
"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-nl36 | 20 | 2 | transformers | 8,340 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-BASE-NL36 (Deep-Narrow version)
T5-Efficient-BASE-NL36 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... |
google/t5-xxl-ssm | 83c5def4267e990544af2a0b3b9cc5722fb3e816 | 2020-12-07T07:51:13.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"dataset:wikipedia",
"arxiv:2002.08909",
"arxiv:1910.10683",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-xxl-ssm | 20 | 2 | transformers | 8,341 | ---
language: en
datasets:
- c4
- wikipedia
license: apache-2.0
---
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) for **Closed Book Question Answering**.
The model was pre-trained using T5's denoising objective on [C4](https://huggingface.co/datasets/c4) and subsequently a... |
google/tapas-large-masklm | c9bbd6020a3b5ac14f389fa0e323f33a2148aa22 | 2021-11-29T14:40:21.000Z | [
"pytorch",
"tf",
"tapas",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | google | null | google/tapas-large-masklm | 20 | null | transformers | 8,342 | This model corresponds to **tapas_masklm_large_reset** of the [original repository](https://github.com/google-research/tapas).
Here's how you can use it:
```python
from transformers import TapasTokenizer, TapasForMaskedLM
import pandas as pd
import torch
tokenizer = TapasTokenizer.from_pretrained("google/tapas-large... |
huggingtweets/playboicarti | 8159608133356ff56f7bb720d2e2349f5e28b947 | 2021-06-14T03:47:42.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/playboicarti | 20 | null | transformers | 8,343 | ---
language: en
thumbnail: https://www.huggingtweets.com/playboicarti/1623642457997/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; w... |
huggingtweets/sodaag | f86eb90c1c653b0cf5795d4d83e92e7aebfa5b5e | 2021-05-22T23:24:50.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/sodaag | 20 | null | transformers | 8,344 | ---
language: en
thumbnail: https://www.huggingtweets.com/sodaag/1621031819814/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: ... |
hyunwoongko/ctrlsum-arxiv | 8d4e245ddfefcf7d0ad9e3f85ceb505fa6175f6f | 2021-03-21T15:56:59.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | hyunwoongko | null | hyunwoongko/ctrlsum-arxiv | 20 | null | transformers | 8,345 | Entry not found |
jakobwes/finance-gpt2 | 91993ffac878525968f3efd3b783d3bd3f166dd7 | 2021-10-26T23:08:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | jakobwes | null | jakobwes/finance-gpt2 | 20 | null | transformers | 8,346 | Entry not found |
jkulhanek/augpt-bigdata | 5e08917420a0e4687b710c0060ec75f092a58300 | 2021-05-23T05:57:14.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | jkulhanek | null | jkulhanek/augpt-bigdata | 20 | null | transformers | 8,347 | Entry not found |
junnyu/roformer_chinese_char_base | 060ed0465e729f68583256a1ae3ea146600b65b6 | 2022-01-04T11:45:40.000Z | [
"pytorch",
"tf",
"jax",
"roformer",
"fill-mask",
"zh",
"arxiv:2104.09864",
"transformers",
"tf2.0",
"autotrain_compatible"
] | fill-mask | false | junnyu | null | junnyu/roformer_chinese_char_base | 20 | null | transformers | 8,348 | ---
language: zh
tags:
- roformer
- pytorch
- tf2.0
widget:
- text: "今天[MASK]很好，我想去公园玩！"
---
## 介绍
### tf版本
https://github.com/ZhuiyiTechnology/roformer
### pytorch版本+tf2.0版本
https://github.com/JunnYu/RoFormer_pytorch
## pytorch使用
```python
import torch
from transformers import RoFormerForMaskedLM, RoFormerTokenizer... |
justin871030/bert-base-uncased-goemotions-original-finetuned | 6048bf9eb71d391855123b898759f70565c38ca7 | 2022-02-09T17:17:55.000Z | [
"pytorch",
"bert",
"en",
"dataset:go_emotions",
"transformers",
"go-emotion",
"text-classification",
"license:mit"
] | text-classification | false | justin871030 | null | justin871030/bert-base-uncased-goemotions-original-finetuned | 20 | null | transformers | 8,349 | ---
language: en
tags:
- go-emotion
- text-classification
- pytorch
datasets:
- go_emotions
metrics:
- f1
widget:
- text: "Thanks for giving advice to the people who need it! 👌🙏"
license: mit
---
## Model Description
1. Based on the uncased BERT pretrained model with a linear output layer.
2. Added several commonly-... |
kittinan/exercise-feedback-classification | d07afbd08ce080ab591d85db48cc080cc90b5fae | 2021-07-08T17:44:43.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | kittinan | null | kittinan/exercise-feedback-classification | 20 | null | transformers | 8,350 | # Reddit exercise feedback classification
Model to classify Reddit's comments for exercise feedback. Current classes are good, correction, bad posture, not informative. If you want to use it locally,
### Usage:
```py
from transformers import pipeline
classifier = pipeline("text-classification", "kittinan/exercise-fee... |
lgris/sew-tiny-portuguese-cv7 | 7a1ce3db82c3b45c111c49b73cde479a3885c1eb | 2022-03-23T18:27:38.000Z | [
"pytorch",
"tensorboard",
"sew",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | lgris | null | lgris/sew-tiny-portuguese-cv7 | 20 | null | transformers | 8,351 | ---
language:
- pt
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
- pt
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: sew-tiny-portuguese-cv7
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
da... |
lucone83/deep-metal | 2c505f15e7defa84079e8d6aeb5366f6b6187649 | 2021-05-23T08:36:22.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | lucone83 | null | lucone83/deep-metal | 20 | null | transformers | 8,352 | ## Model description
**DeepMetal** is a model capable of generating lyrics taylored for heavy metal songs.
The model is based on the [OpenAI GPT-2](https://huggingface.co/gpt2) and has been finetuned on a dataset of 141,718 heavy metal songs lyrics.
More info about the project can be found in the [official GitHub repo... |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_wu_7k_grad_adam_mask | 0a5dbf07ec265578f166ac4ea40c644ad236e329 | 2021-10-31T11:03:18.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_wu_7k_grad_adam_mask | 20 | null | transformers | 8,353 | Entry not found |
m3hrdadfi/wav2vec2-base-100k-eating-sound-collection | 18578163489775737e5adbbe1c207f52c221814f | 2021-07-06T10:26:03.000Z | [
"pytorch",
"wav2vec2",
"transformers",
"audio",
"automatic-speech-recognition",
"audio-classification"
] | automatic-speech-recognition | false | m3hrdadfi | null | m3hrdadfi/wav2vec2-base-100k-eating-sound-collection | 20 | null | transformers | 8,354 | ---
tags:
- audio
- automatic-speech-recognition
- audio-classification
---
# Eating Sound Classification using Wav2Vec 2.0
## How to use
### Requirements
```bash
# requirement packages
!pip install git+https://github.com/huggingface/datasets.git
!pip install git+https://github.com/huggingface/transformers.git
!pi... |
madlag/bert-base-uncased-squadv1-x2.44-f87.7-d26-hybrid-filled-v1 | 6888c84f95b7cc8c585e7bfe306c9ceec3532899 | 2021-08-31T12:00:08.000Z | [
"pytorch",
"tf",
"bert",
"question-answering",
"en",
"dataset:squad",
"transformers",
"license:mit",
"autotrain_compatible"
] | question-answering | false | madlag | null | madlag/bert-base-uncased-squadv1-x2.44-f87.7-d26-hybrid-filled-v1 | 20 | null | transformers | 8,355 | ---
language: en
thumbnail:
license: mit
tags:
- question-answering
-
-
datasets:
- squad
metrics:
- squad
widget:
- text: "Where is the Eiffel Tower located?"
context: "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France. It is named after the engineer Gustave Eiffel, whose compa... |
mbeukman/xlm-roberta-base-finetuned-ner-luganda | b96b7e908549607c6c2086d4b05becc5e4c84f92 | 2021-11-25T09:04:33.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"lug",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-ner-luganda | 20 | null | transformers | 8,356 | ---
language:
- lug
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Empaka zaakubeera mu kibuga Liverpool e Bungereza , okutandika nga July 12 ."
---
# xlm-roberta-base-finetuned-ner-luganda
This is a token classification (specifically NER) model that fine-tuned [xlm-roberta-... |
mrm8488/camembert-base-finetuned-movie-review-sentiment-analysis | bc3bf95e9fcf6db8f25b574de0764823a45d7661 | 2021-06-21T10:15:26.000Z | [
"pytorch",
"camembert",
"text-classification",
"transformers"
] | text-classification | false | mrm8488 | null | mrm8488/camembert-base-finetuned-movie-review-sentiment-analysis | 20 | null | transformers | 8,357 | Entry not found |
nlplab/political-entity-recognizer | 41954a333c1cde3a4ade560a6f38488ec2f4f7e5 | 2021-12-20T05:59:07.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | nlplab | null | nlplab/political-entity-recognizer | 20 | null | transformers | 8,358 | Entry not found |
novakat/nerkor-cars-onpp-hubert | c465f3ddeec84e54e7d6f5f519cecbd4fcfd0a61 | 2022-07-04T21:19:05.000Z | [
"pytorch",
"bert",
"hu",
"transformers",
"token-classification",
"license:gpl"
] | token-classification | false | novakat | null | novakat/nerkor-cars-onpp-hubert | 20 | null | transformers | 8,359 | ---
language:
- hu
tags:
- token-classification
license: gpl
metrics:
- F1
widget:
- text: "A jótékonysági szervezet által idézett Forbes-adatok szerint a világ tíz leggazdagabb embere: Elon Musk (Tesla, SpaceX), Jeff Bezos (Amazon, Blue Origin), Bernard Arnault és családja (LVMH, azaz Louis Vuitton és Moët Henness... |
pbmstrk/t5-large-arxiv-abstract-title | e550e89d83f75917f100ec69d9485ac97e172c40 | 2020-11-23T15:57:50.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | pbmstrk | null | pbmstrk/t5-large-arxiv-abstract-title | 20 | 1 | transformers | 8,360 | Entry not found |
peggyhuang/distilbert-base-uncased-coqa | 455fe8347f28f4b7fe6789f8143219a7739e40e3 | 2021-11-19T09:10:23.000Z | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | peggyhuang | null | peggyhuang/distilbert-base-uncased-coqa | 20 | null | transformers | 8,361 | Entry not found |
persiannlp/mt5-small-parsinlu-snli-entailment | 88515fb575eaadaf33e89d330ccbbdec8da51646 | 2021-09-23T16:20:43.000Z | [
"pytorch",
"t5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"dataset:snli",
"transformers",
"entailment",
"mt5",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-small-parsinlu-snli-entailment | 20 | null | transformers | 8,362 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- snli
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailmen... |
proycon/bert-lemma-cased-cgn_elex-nld | 689d95b199f0fc8c839ca36b488782d31ad68898 | 2021-05-20T03:02:48.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | proycon | null | proycon/bert-lemma-cased-cgn_elex-nld | 20 | null | transformers | 8,363 | Entry not found |
proycon/robbert-pos-cased-deepfrog-nld | a8caaaf3bec3345e949e339fa5a11344f67e6b5f | 2021-05-20T19:42:26.000Z | [
"pytorch",
"jax",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | proycon | null | proycon/robbert-pos-cased-deepfrog-nld | 20 | null | transformers | 8,364 | Entry not found |
pysentimiento/robertuito-base-deacc | 9ec253c618699a0daa497306282ff02291987a0f | 2021-11-19T13:58:19.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2111.09453",
"transformers",
"autotrain_compatible"
] | fill-mask | false | pysentimiento | null | pysentimiento/robertuito-base-deacc | 20 | null | transformers | 8,365 | # robertuito-base-deacc
# 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 content in Spanish, train... |
qwant/fralbert-base | 79e16a36e0ed5416a4a1912befcfd3bc90a2653e | 2021-09-24T13:21:21.000Z | [
"pytorch",
"albert",
"fill-mask",
"fr",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | qwant | null | qwant/fralbert-base | 20 | 2 | transformers | 8,366 | ---
language: fr
license: apache-2.0
datasets:
- wikipedia
---
# FrALBERT Base
Pretrained model on French language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1909.11942) and first released in
[this repository](https://github.com/google-research/albert). T... |
rohanrajpal/bert-base-en-hi-codemix-cased | cb56cad2618dea26f40bbc6ca02a68359957ea58 | 2021-05-19T00:31:33.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"hi",
"en",
"dataset:SAIL 2017",
"transformers",
"es",
"codemix",
"license:apache-2.0"
] | text-classification | false | rohanrajpal | null | rohanrajpal/bert-base-en-hi-codemix-cased | 20 | null | transformers | 8,367 | ---
language:
- hi
- en
tags:
- es
- en
- codemix
license: "apache-2.0"
datasets:
- SAIL 2017
metrics:
- fscore
- accuracy
- precision
- recall
---
# BERT codemixed base model for Hinglish (cased)
This model was built using [lingualytics](https://github.com/lingualytics/py-lingualytics), an open-source library that s... |
rsvp-ai/bertserini-roberta-base | fcfa01487d28f6bc9487d3ddf735615067c11512 | 2021-05-20T19:56:06.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | rsvp-ai | null | rsvp-ai/bertserini-roberta-base | 20 | null | transformers | 8,368 | Entry not found |
rti-international/rota | f41c751002747268eec1f9bf7ad10dc94028b4a9 | 2021-05-20T19:57:32.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"en",
"transformers"
] | text-classification | false | rti-international | null | rti-international/rota | 20 | 1 | transformers | 8,369 | ---
language:
- en
widget:
- text: theft 3
- text: forgery
- text: unlawful possession short-barreled shotgun
- text: criminal trespass 2nd degree
- text: eluding a police vehicle
- text: upcs synthetic narcotic
---
# ROTA
## Rapid Offense Text Autocoder
[![HuggingFace Models](https://img.shields.io/badge/%F0%9F%A4%... |
sagorsarker/mbert-bengali-tydiqa-qa | 53972067f6fe358254b92d2a62554b9ebd55c979 | 2021-09-22T09:37:34.000Z | [
"pytorch",
"bert",
"question-answering",
"bn",
"dataset:tydiqa",
"transformers",
"mbert",
"bengali",
"bangla",
"qa",
"license:mit",
"autotrain_compatible"
] | question-answering | false | sagorsarker | null | sagorsarker/mbert-bengali-tydiqa-qa | 20 | null | transformers | 8,370 | ---
language: bn
tags:
- mbert
- bengali
- question-answering
- bangla
- qa
license: mit
datasets:
- tydiqa
---
# mBERT Bengali Question Answering
`mBERT-Bengali-Tydiqa-QA` is a question answering model fine-tuning [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) model with [tydi... |
salesken/similarity-eng-hin_latin | 9de26c34be908934dee73e289cf0bc6f181f88a7 | 2021-08-02T10:16:14.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | salesken | null | salesken/similarity-eng-hin_latin | 20 | 1 | sentence-transformers | 8,371 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
widget:
- source_sentence: "hum baccho ko online classes ke liye free laptop dete hai"
- sentences: ["we provide free laptops to kids for online classes", "hum kids ko padhne ke liye free laptop... |
seduerr/t5-small-pytorch | 35ec79eeed1f44ff077508b09eb24bf1730a7706 | 2021-04-06T04:48:50.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"fr",
"ro",
"de",
"dataset:c4",
"arxiv:1910.10683",
"transformers",
"summarization",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | seduerr | null | seduerr/t5-small-pytorch | 20 | null | transformers | 8,372 | ---
language:
- en
- fr
- ro
- de
datasets:
- c4
tags:
- summarization
- translation
license: apache-2.0
---
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html)
Pretraining Dataset: [C4](https://huggingface.co/datasets/c4)
Other Community Checkpoints: [here](https://huggingfa... |
sentence-transformers/xlm-r-base-en-ko-nli-ststb | 0de1923e7b7682773de2b0e75d07e8a6cfb930b8 | 2022-06-16T00:57:04.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/xlm-r-base-en-ko-nli-ststb | 20 | 0 | sentence-transformers | 8,373 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
**⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net... |
speech-seq2seq/wav2vec2-2-bert-large-no-adapter | 87fdda593303e200e8919790b07e1883f1f13ea9 | 2022-02-21T17:49:39.000Z | [
"pytorch",
"tensorboard",
"speech-encoder-decoder",
"automatic-speech-recognition",
"dataset:librispeech_asr",
"transformers",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | speech-seq2seq | null | speech-seq2seq/wav2vec2-2-bert-large-no-adapter | 20 | null | transformers | 8,374 | ---
tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: ''
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. -->
#
This model was trained... |
speechbrain/asr-wav2vec2-commonvoice-it | 24819ad91a6b8a3bab4008820ea57f4afd72afdd | 2021-12-18T09:19:52.000Z | [
"wav2vec2",
"feature-extraction",
"en",
"dataset:commonvoice",
"arxiv:2106.04624",
"speechbrain",
"CTC",
"Attention",
"pytorch",
"Transformer",
"license:apache-2.0",
"automatic-speech-recognition"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-wav2vec2-commonvoice-it | 20 | null | speechbrain | 8,375 | ---
language: "en"
thumbnail:
pipeline_tag: automatic-speech-recognition
tags:
- CTC
- Attention
- pytorch
- speechbrain
- Transformer
license: "apache-2.0"
datasets:
- commonvoice
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large... |
sshasnain/finetune-wav2vec2-large-xlsr-bengali | bb32e8c5003c42a76d53ca0f22ad327867da5d7e | 2022-01-30T07:55:29.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"Bengali",
"dataset:custom",
"transformers",
"bn",
"audio",
"speech",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | sshasnain | null | sshasnain/finetune-wav2vec2-large-xlsr-bengali | 20 | null | transformers | 8,376 | ---
language: Bengali
datasets:
- custom
metrics:
- wer
tags:
- bn
- audio
- automatic-speech-recognition
- speech
license: apache-2.0
model-index:
- name: finetune-wav2vec2-large-xlsr-bengali
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: custom
... |
symanto/sn-mpnet-base-snli-mnli | 0b6e31e1eeefd5306d1157b1bee4af3df63547da | 2021-09-30T11:34:19.000Z | [
"pytorch",
"mpnet",
"feature-extraction",
"en",
"dataset:SNLI",
"dataset:MNLI",
"sentence-transformers",
"zero-shot-classification",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | symanto | null | symanto/sn-mpnet-base-snli-mnli | 20 | null | sentence-transformers | 8,377 | ---
language:
- en
datasets:
- SNLI
- MNLI
pipeline_tag: sentence-similarity
tags:
- zero-shot-classification
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
A Siamese network model trained for zero-shot and few-shot text classification.
The base model is [mpnet-base](https://... |
uclanlp/plbart-single_task-compiled-summarization | bcfd53d6a25a3ac8a7602e4ecf80a788bf5eadb6 | 2022-03-02T07:13:00.000Z | [
"pytorch",
"plbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uclanlp | null | uclanlp/plbart-single_task-compiled-summarization | 20 | null | transformers | 8,378 | Entry not found |
yaoyinnan/bert-base-chinese-covid19 | 3ee92e1e63141d64935f904b67c4f6fd14c92083 | 2021-05-20T09:18:12.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | yaoyinnan | null | yaoyinnan/bert-base-chinese-covid19 | 20 | null | transformers | 8,379 | Entry not found |
youzanai/bert-product-title-chinese | b42a1dd0733c2936276cebf90a0bbb69dce9a83d | 2022-03-18T06:19:06.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | youzanai | null | youzanai/bert-product-title-chinese | 20 | 1 | transformers | 8,380 | 基于有赞商品标题语料训练的bert模型。
模型示例代码参考 https://github.com/youzanai/trexpark |
zlucia/bert-double | 0ce1a5b13ad6781ac7784521d1b56e1f48c89cf7 | 2021-07-02T05:54:19.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"pretraining",
"en",
"arxiv:2104.08671",
"arxiv:1810.04805",
"arxiv:1903.10676",
"transformers",
"fill-mask"
] | fill-mask | false | zlucia | null | zlucia/bert-double | 20 | 1 | transformers | 8,381 | ---
language: en
pipeline_tag: fill-mask
---
### BERT (double)
Model and tokenizer files for BERT (double) model from [When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset](https://arxiv.org/abs/2104.08671).
### Training Data
BERT (double) is pretrained using the same Englis... |
inovex/multi2convai-quality-fr-bert | c9a42eabf6899ddc6e41804e169995cc7ff59687 | 2022-03-01T09:01:32.000Z | [
"pytorch",
"bert",
"text-classification",
"fr",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-quality-fr-bert | 20 | null | transformers | 8,382 | ---
tags:
- text-classification
widget:
- text: "Lancer le programme"
license: mit
language: fr
---
# Multi2ConvAI-Quality: finetuned Bert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2con... |
inovex/multi2convai-quality-fr-mbert | 0ce62defbf23e328000a95f4db498fff33815516 | 2022-03-01T09:01:51.000Z | [
"pytorch",
"bert",
"text-classification",
"fr",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-quality-fr-mbert | 20 | null | transformers | 8,383 | ---
tags:
- text-classification
widget:
- text: "Lancer le programme"
license: mit
language: fr
---
# Multi2ConvAI-Quality: finetuned MBert for French
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2co... |
Davlan/xlm-roberta-base-sadilar-ner | bd751e53d6b7780a71d13df658b84721b6ecdb9a | 2022-02-25T16:08:42.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"af",
"nr",
"nso",
"ss",
"st",
"tn",
"ts",
"ve",
"xh",
"zu",
"multilingual",
"dataset:masakhaner",
"transformers",
"autotrain_compatible"
] | token-classification | false | Davlan | null | Davlan/xlm-roberta-base-sadilar-ner | 20 | 1 | transformers | 8,384 | Hugging Face's logo
---
language:
- af
- nr
- nso
- ss
- st
- tn
- ts
- ve
- xh
- zu
- multilingual
datasets:
- masakhaner
---
# xlm-roberta-base-sadilar-ner
## Model description
**xlm-roberta-base-sadilar-ner** is the first **Named Entity Recognition** model for 10 South African languages (Afri... |
KheireddineDaouadi/ZeroAraElectra | f67008d3db125c704dafdb85950362a8004e25bb | 2022-02-26T18:40:11.000Z | [
"pytorch",
"electra",
"text-classification",
"ar",
"dataset:xnli",
"transformers",
"zero-shot-classification",
"nli",
"license:other"
] | zero-shot-classification | false | KheireddineDaouadi | null | KheireddineDaouadi/ZeroAraElectra | 20 | null | transformers | 8,385 | ---
language: ar
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- xnli
pipeline_tag: zero-shot-classification
license: other
---
|
orzhan/ruroberta-ruatd-binary | a2aebdf6a151759c6afd76ab378d97db5ea04d8d | 2022-03-09T15:36:04.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | orzhan | null | orzhan/ruroberta-ruatd-binary | 20 | null | transformers | 8,386 | sberbank-ai/ruRoberta-large fine-tuned for Russian Artificial Text Detection shared task
|
tinparadox/NER-en-vi-it-es | e9154524efee344a1bdf0f40dc019f3bd806a4f4 | 2022-03-10T04:07:29.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tinparadox | null | tinparadox/NER-en-vi-it-es | 20 | null | transformers | 8,387 | Entry not found |
KoichiYasuoka/bert-base-german-upos | db200553b2ac186e9809fbc9d80bf0261f4de684 | 2022-03-11T10:14:41.000Z | [
"pytorch",
"bert",
"token-classification",
"de",
"dataset:universal_dependencies",
"transformers",
"german",
"pos",
"dependency-parsing",
"license:mit",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/bert-base-german-upos | 20 | null | transformers | 8,388 | ---
language:
- "de"
tags:
- "german"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "mit"
pipeline_tag: "token-classification"
---
# bert-base-german-upos
## Model Description
This is a BERT model pre-trained with [UD_German-HDT](https://github.com/UniversalDep... |
cambridgeltl/c2_mbert_de2tr_5k | 4976984f53d6deb711df1a51e3ad936407c815bf | 2022-03-10T14:11:49.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/c2_mbert_de2tr_5k | 20 | null | transformers | 8,389 | Entry not found |
kapilchauhan/efl-finetuned-cola | 4e8796b0ac55a03a94f00d489954cf19abe46e24 | 2022-03-14T05:32:44.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | kapilchauhan | null | kapilchauhan/efl-finetuned-cola | 20 | null | transformers | 8,390 | ---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: efl-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
- name: Matthews Correlation
... |
huggingtweets/temapex | 3d801fbb179e2d4d39916bb034fc8da97af96096 | 2022-05-08T15:33:31.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/temapex | 20 | null | transformers | 8,391 | ---
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... |
davidmasip/racism | fa50338fad3d03ccf41af566b6b6d865f9ee35b3 | 2022-03-31T06:56:46.000Z | [
"pytorch",
"roberta",
"text-classification",
"es",
"transformers",
"license:cc"
] | text-classification | false | davidmasip | null | davidmasip/racism | 20 | null | transformers | 8,392 | ---
license: cc
language: es
widget:
- text: "Me cae muy bien."
example_title: "Non-racist example"
- text: "Unos menas agreden a una mujer."
example_title: "Racist example"
---
Model to predict whether a given text is racist or not:
* `LABEL_0` output indicates non-racist text
* `LABEL_1` output i... |
dannyvas23/clasificacion-texto-suicida-finetuned-amazon-review | da5eea27f0cf5447483cf8ee2bb87f2f6e03f072 | 2022-03-26T17:12:23.000Z | [
"pytorch",
"tensorboard",
"electra",
"text-classification",
"es",
"transformers",
"generated_from_trainer",
"sentiment",
"emotion",
"model-index"
] | text-classification | false | dannyvas23 | null | dannyvas23/clasificacion-texto-suicida-finetuned-amazon-review | 20 | 2 | transformers | 8,393 | ---
language: "es"
tags:
- generated_from_trainer
- sentiment
- emotion
widget:
- text: "no me gusta esta vida."
example_title: "Ejemplo 1"
- text: "odio estar ahi"
example_title: "Ejemplo 2"
- text: "me siento triste por no poder viajar"
example_title: "Ejemplo 3"
metrics:
- accuracy
model-index:
- name: clasif... |
huggingartists/kendrick-lamar | ba0f5191dbd3680bbf4aed6cb416f2eec5b3d7a3 | 2022-05-23T21:44:07.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/kendrick-lamar",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/kendrick-lamar | 20 | null | transformers | 8,394 | ---
language: en
datasets:
- huggingartists/kendrick-lamar
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; h... |
microsoft/amos | fcdd551fc8568c22b34630aa893772873b36f233 | 2022-03-24T01:24:38.000Z | [
"pytorch",
"transformers",
"license:mit"
] | null | false | microsoft | null | microsoft/amos | 20 | null | transformers | 8,395 | ---
license: mit
---
# Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
This model card contains the AMOS model (**base++** version) proposed in [this paper](). The official GitHub repository can be found [here](https://github.com/microsoft/AMOS).
# Citation
If you find this ... |
hackathon-pln-es/readability-es-sentences | 841de37a6c8676a8d1156983686100cfaf9d6cc4 | 2022-04-04T10:41:09.000Z | [
"pytorch",
"roberta",
"text-classification",
"es",
"transformers",
"spanish",
"bertin",
"license:cc-by-4.0"
] | text-classification | false | hackathon-pln-es | null | hackathon-pln-es/readability-es-sentences | 20 | 3 | transformers | 8,396 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
- bertin
pipeline_tag: text-classification
widget:
- text: La ciencia nos enseña, en efecto, a someter nuestra razón a la verdad y a conocer y juzgar las cosas como son, es decir, como ellas mismas eligen ser y no como quisiéramos que fueran.
---
# Readabil... |
huggingtweets/stillconor | 185c206f0cada304d89289e15fc6f5c24f5893c7 | 2022-03-31T17:49:05.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/stillconor | 20 | null | transformers | 8,397 | ---
language: en
thumbnail: http://www.huggingtweets.com/stillconor/1648748939988/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; widt... |
McGill-NLP/bart-qg-nq-checkpoint | 250891747ba149035e3ebb06b5719aeb045e1dbe | 2022-04-01T17:35:04.000Z | [
"pytorch",
"bart",
"text2text-generation",
"arxiv:1910.13461",
"transformers",
"license:cc-by-4.0",
"autotrain_compatible"
] | text2text-generation | false | McGill-NLP | null | McGill-NLP/bart-qg-nq-checkpoint | 20 | null | transformers | 8,398 | ---
license: cc-by-4.0
---
# BART-base fine-tuned on NaturalQuestions for **Question Generation**
[BART Model](https://arxiv.org/pdf/1910.13461.pdf) fine-tuned on [Google NaturalQuestions](https://ai.google.com/research/NaturalQuestions/) for **Question Generation** by treating long answer as input, and question ... |
SkyR/wikineural-multilingual-ner | 635890a3dab38c89d64a23430d6709aaa93296cf | 2022-04-11T18:13:27.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | SkyR | null | SkyR/wikineural-multilingual-ner | 20 | null | transformers | 8,399 | Entry not found |
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