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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
facebook/levit-384 | f71571497ab7affc0f78cc89432b0bd94704ec22 | 2022-06-01T13:20:59.000Z | [
"pytorch",
"levit",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2104.01136",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/levit-384 | 188 | null | transformers | 3,700 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https... |
Helsinki-NLP/opus-mt-nl-fr | a53c0a8a8bee7266a39fd56d737a6c9996dc1909 | 2021-09-10T13:59:19.000Z | [
"pytorch",
"marian",
"text2text-generation",
"nl",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-nl-fr | 187 | null | transformers | 3,701 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-nl-fr
* source languages: nl
* target languages: fr
* OPUS readme: [nl-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/nl-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
J-Chiang/DialoGPT-small-thor | 4baaa45636fc157c7a36ba396e4542d29368eaec | 2021-09-05T16:33:02.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | J-Chiang | null | J-Chiang/DialoGPT-small-thor | 187 | null | transformers | 3,702 | ---
tags:
- conversational
---
# Thor DialogGPT Model |
deepset/tinybert-6l-768d-squad2 | d2f54c1d54eb6d509bd108987df3e7ebb3d25e6f | 2022-07-26T08:31:16.000Z | [
"pytorch",
"bert",
"question-answering",
"en",
"dataset:squad_v2",
"arxiv:1909.10351",
"transformers",
"exbert",
"license:mit",
"model-index",
"autotrain_compatible"
] | question-answering | false | deepset | null | deepset/tinybert-6l-768d-squad2 | 187 | null | transformers | 3,703 | ---
language: en
datasets:
- squad_v2
license: mit
thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
tags:
- exbert
model-index:
- name: deepset/tinybert-6l-768d-squad2
results:
- task:
type: question-answering
name: Question Answering
... |
naclbit/gpt-j-japanese-6.8b | 135e2c5420171f09636ba25f45b9934c70278728 | 2021-11-10T15:28:57.000Z | [
"gptj",
"text-generation",
"ja",
"arxiv:2104.09864",
"transformers",
"japanese",
"pytorch",
"t5tokenizer",
"sentencepiece",
"license:apache-2.0"
] | text-generation | false | naclbit | null | naclbit/gpt-j-japanese-6.8b | 187 | 3 | transformers | 3,704 | ---
language:
- ja
tags:
- japanese
- text-generation
- gptj
- pytorch
- transformers
- t5tokenizer
- sentencepiece
license: apache-2.0
---
This pre-trained model is work in progress! Model weight download will be available in the future.
A 6.8 billion parameter pre-trained model for Japanese language, based on El... |
razent/spbert-mlm-wso-base | 0ac86fd5e116460e62e422ad9f50736367f3e36c | 2022-03-15T03:25:41.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"code",
"arxiv:2106.09997",
"transformers",
"question-answering",
"knowledge-graph",
"autotrain_compatible"
] | question-answering | false | razent | null | razent/spbert-mlm-wso-base | 187 | null | transformers | 3,705 | ---
language:
- code
tags:
- question-answering
- knowledge-graph
---
# SPBERT MLM+WSO (Initialized)
## Introduction
Paper: [SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs](https://arxiv.org/abs/2106.09997)
Authors: _Hieu Tran, Long Phan, James Anibal, Binh T.... |
sismetanin/sbert-ru-sentiment-rureviews | b4aaa41ae90fe37f9caa4c8b769de0720d65f62a | 2021-05-20T06:35:54.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"ru",
"transformers",
"sentiment analysis",
"Russian"
] | text-classification | false | sismetanin | null | sismetanin/sbert-ru-sentiment-rureviews | 187 | 1 | transformers | 3,706 | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## SBERT-ru-sentiment-RuReviews
SBERT-ru-sentiment-RuReviews is a [SBERT-Large](https://huggingface.co/sberbank-ai/sbert_large_nlu_ru) model fine-tuned on [RuReviews dataset](https://github.com/sismetanin/rureviews) of Russian-language reviews from the ”Wom... |
svalabs/bi-electra-ms-marco-german-uncased | 02c3286af86f4b09bff0d6e59f61581f3b54dbf7 | 2021-06-14T07:46:23.000Z | [
"pytorch",
"electra",
"feature-extraction",
"arxiv:1908.10084",
"arxiv:1611.09268",
"arxiv:2104.08663",
"arxiv:2104.12741",
"transformers"
] | feature-extraction | false | svalabs | null | svalabs/bi-electra-ms-marco-german-uncased | 187 | 3 | transformers | 3,707 | # SVALabs - German Uncased Electra Bi-Encoder
In this repository, we present our german, uncased bi-encoder for Passage Retrieval.
This model was trained on the basis of the german electra uncased model from the [german-nlp-group](https://huggingface.co/german-nlp-group/electra-base-german-uncased) and finetuned as a... |
allenai/PRIMERA-wcep | 8d70caf941f521ae3238d05277812b9a38a2d591 | 2022-06-25T16:04:32.000Z | [
"pytorch",
"tf",
"led",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/PRIMERA-wcep | 187 | 1 | transformers | 3,708 | ---
license: apache-2.0
---
HF-version model for PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization (ACL 2022).
The original code can be found [here](https://github.com/allenai/PRIMER). You can find the script and notebook to train/evaluate the model in the original github rep... |
Helsinki-NLP/opus-mt-ar-fr | 0ef20fb1109cc990302c5a660af876dc2874e862 | 2021-09-09T21:26:19.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ar",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ar-fr | 186 | null | transformers | 3,709 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ar-fr
* source languages: ar
* target languages: fr
* OPUS readme: [ar-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ar-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
tugstugi/bert-base-mongolian-cased | f07c2d5cb25c1fc6baac69a875e8e1bbd040872a | 2021-05-20T08:12:07.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"mn",
"arxiv:1810.04805",
"transformers",
"mongolian",
"cased",
"autotrain_compatible"
] | fill-mask | false | tugstugi | null | tugstugi/bert-base-mongolian-cased | 186 | null | transformers | 3,710 | ---
language: "mn"
tags:
- bert
- mongolian
- cased
---
# BERT-BASE-MONGOLIAN-CASED
[Link to Official Mongolian-BERT repo](https://github.com/tugstugi/mongolian-bert)
## Model description
This repository contains pre-trained Mongolian [BERT](https://arxiv.org/abs/1810.04805) models trained by [tugstugi](https://githu... |
xiaoheiqaq/DialoGPT-mediumJojo | 5b0d2080dc7aff57fb88bbcbeac4db2ca616cb16 | 2021-09-24T14:51:26.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | xiaoheiqaq | null | xiaoheiqaq/DialoGPT-mediumJojo | 186 | null | transformers | 3,711 | ---
tags:
- conversational
---
# Joseph Joestar DialoGPT Model |
voidful/mhubert-base | f6b161b74babb312406f85d63c9982285a441f06 | 2022-06-22T08:18:17.000Z | [
"pytorch",
"hubert",
"feature-extraction",
"transformers"
] | feature-extraction | false | voidful | null | voidful/mhubert-base | 186 | null | transformers | 3,712 | # mhubert-base
* the checkpoint converted from [textless s2st real data](https://github.com/facebookresearch/fairseq/blob/b5a039c292facba9c73f59ff34621ec131d82341/examples/speech_to_speech/docs/textless_s2st_real_data.md)
## usage:
```
asrp==0.0.35 # extracted from fairseq repo
```
```python=
# https://huggingfac... |
dominguesm/bert-restore-punctuation-ptbr | b02fa886fceb570b968e122cd425025ef4f59bce | 2022-07-14T16:01:58.000Z | [
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:wiki_lingua",
"transformers",
"named-entity-recognition",
"Transformer",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | dominguesm | null | dominguesm/bert-restore-punctuation-ptbr | 186 | 1 | transformers | 3,713 | ---
language:
- pt
license: cc-by-4.0
datasets:
- wiki_lingua
thumbnail: null
tags:
- named-entity-recognition
- Transformer
- pytorch
- bert
metrics:
- f1
- precision
- recall
model-index:
- name: rpunct-ptbr
results:
- task:
type: named-entity-recognition
dataset:
type: wiki_lingua
name: wik... |
nickprock/distilbert-base-uncased-banking77-classification | 4a2b896807442154741d09d2edba1a3857fa0d4e | 2022-07-21T12:44:23.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:banking77",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | nickprock | null | nickprock/distilbert-base-uncased-banking77-classification | 186 | null | transformers | 3,714 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-banking77-classification
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: banking77
type: banking77
args: defaul... |
Helsinki-NLP/opus-mt-fr-ar | dc918d744b14d4a3f9661092baf0c2133acc1b4b | 2021-01-18T08:41:25.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fr",
"ar",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-fr-ar | 185 | null | transformers | 3,715 | ---
language:
- fr
- ar
tags:
- translation
license: apache-2.0
---
### fra-ara
* source group: French
* target group: Arabic
* OPUS readme: [fra-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-ara/README.md)
* model: transformer
* source language(s): fra
* target language(s): ap... |
Musixmatch/umberto-wikipedia-uncased-v1 | 713d59922ccb4b5fc31a527ce2d785c23533363b | 2021-02-10T09:53:35.000Z | [
"pytorch",
"camembert",
"fill-mask",
"it",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Musixmatch | null | Musixmatch/umberto-wikipedia-uncased-v1 | 185 | 1 | transformers | 3,716 | ---
language: it
---
# UmBERTo Wikipedia Uncased
[UmBERTo](https://github.com/musixmatchresearch/umberto) is a Roberta-based Language Model trained on large Italian Corpora and uses two innovative approaches: SentencePiece and Whole Word Masking. Now available at [github.com/huggingface/transformers](https://huggingf... |
malduwais/distilbert-base-uncased-finetuned-ner | 66ffbe9687f004a1461fce7fd67cbf1972b91837 | 2021-11-28T09:59:58.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | malduwais | null | malduwais/distilbert-base-uncased-finetuned-ner | 185 | null | transformers | 3,717 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conl... |
sayef/fsner-bert-base-uncased | aea2529c44e8f7ab440f5d8ece7c48c7293e00bf | 2022-03-29T14:20:35.000Z | [
"pytorch",
"bert",
"feature-extraction",
"arxiv:2008.10570",
"transformers"
] | feature-extraction | false | sayef | null | sayef/fsner-bert-base-uncased | 185 | 5 | transformers | 3,718 | # FSNER
Implemented by [sayef](https://huggingface.co/sayef).
# Overview
The FSNER model was proposed in [Example-Based Named Entity Recognition](https://arxiv.org/abs/2008.10570) by Morteza
Ziyadi, Yuting Sun, Abhishek Goswami, Jade Huang, Weizhu Chen. To identify entity spans in a new domain, it uses a
train-free ... |
sonoisa/t5-base-japanese-mC4-Wikipedia | cbf67abe3b28b3ec4c32bbead1207cf2366a3c7f | 2021-09-23T16:29:58.000Z | [
"pytorch",
"ja",
"dataset:wikipedia",
"dataset:c4",
"transformers",
"t5",
"text2text-generation",
"seq2seq",
"license:cc-by-sa-4.0"
] | text2text-generation | false | sonoisa | null | sonoisa/t5-base-japanese-mC4-Wikipedia | 185 | 1 | transformers | 3,719 | ---
language: ja
tags:
- t5
- text2text-generation
- seq2seq
license: cc-by-sa-4.0
datasets:
- wikipedia
- c4
---
# 日本語T5事前学習済みモデル
This is a T5 (Text-to-Text Transfer Transformer) model pretrained on Japanese corpus.
次の日本語コーパス（約890GB）を用いて事前学習を行ったT5 (Text-to-Text Transfer Transformer) モデルです。
* [Wikipedia](https://... |
speechbrain/asr-wav2vec2-commonvoice-en | a1a126cc07ff5426a71487a89132bd1b70c7155e | 2022-06-05T17:24:43.000Z | [
"wav2vec2",
"feature-extraction",
"en",
"dataset:commonvoice",
"arxiv:2106.04624",
"speechbrain",
"CTC",
"pytorch",
"Transformer",
"license:apache-2.0",
"automatic-speech-recognition"
] | automatic-speech-recognition | false | speechbrain | null | speechbrain/asr-wav2vec2-commonvoice-en | 185 | 4 | speechbrain | 3,720 | ---
language: "en"
thumbnail:
pipeline_tag: automatic-speech-recognition
tags:
- CTC
- 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&v=2" frameb... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-msa | 9685a2a42a5f777ae91768556e7fe1124819b99f | 2021-10-18T09:44:57.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-msa | 184 | null | transformers | 3,721 | ---
language:
- ar
license: apache-2.0
widget:
- text: 'إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع'
---
# CAMeLBERT-CA POS-MSA Model
## Model description
**CAMeLBERT-CA POS-MSA Model** is a Modern Standard Arabic (MSA) POS tagging model that was built by fine-tuning the [CAMeLBERT-CA](https://hug... |
alenusch/mt5base-ruparaphraser | 827b216941a88188c88ebbe0f35c0aaa87a8f642 | 2020-12-19T17:39:00.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | alenusch | null | alenusch/mt5base-ruparaphraser | 184 | null | transformers | 3,722 | Entry not found |
digio/Twitter4SSE | 91e20090fe4fa7e57fd3ebfad3dd89c9538b5669 | 2021-12-17T09:01:29.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"en",
"arxiv:2110.02030",
"transformers",
"Pytorch",
"Sentence Transformers",
"Transformers",
"license:apache-2.0",
"sentence-similarity"
] | sentence-similarity | false | digio | null | digio/Twitter4SSE | 184 | 1 | transformers | 3,723 | ---
language:
- en
pipeline_tag: sentence-similarity
tags:
- Pytorch
- Sentence Transformers
- Transformers
license: "apache-2.0"
---
# Twitter4SSE
This model maps texts to 768 dimensional dense embeddings that encode semantic similarity.
It was trained with Multiple Negatives Ranking Loss (MNRL) on a Twitter dat... |
philschmid/distilbert-base-multilingual-cased-sentiment | b45a713783e49ac09c94dfda4bff847f4ad771c5 | 2022-01-24T12:14:53.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:amazon_reviews_multi",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | philschmid | null | philschmid/distilbert-base-multilingual-cased-sentiment | 184 | null | transformers | 3,724 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type... |
facebook/maskformer-swin-base-ade | 4f7b799a3566c531042bb79874739fdc0522e20e | 2022-04-04T16:01:58.000Z | [
"pytorch",
"maskformer",
"dataset:ade-20k",
"arxiv:2107.06278",
"transformers",
"vision",
"image-segmentatiom",
"license:apache-2.0"
] | null | false | facebook | null | facebook/maskformer-swin-base-ade | 184 | null | transformers | 3,725 | ---
license: apache-2.0
tags:
- vision
- image-segmentatiom
datasets:
- ade-20k
widget:
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00000001.jpg
example_title: House
- src: https://huggingface.co/datasets/hf-internal-testing/fixtures_ade20k/resolve/main/ADE_val_00... |
BlackSamorez/ebanko-base | f21b1aa7d0a080a8cce0f154dcc9f9eae4888eac | 2022-04-29T12:29:02.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ru",
"transformers",
"PyTorch",
"Transformers",
"autotrain_compatible"
] | text2text-generation | false | BlackSamorez | null | BlackSamorez/ebanko-base | 184 | null | transformers | 3,726 | ---
language:
- ru
tags:
- PyTorch
- Transformers
---
# ebanko-base
Model was finetuned by [black_samorez](https://github.com/BlackSamorez).
Based off [sberbank-ai/ruT5-base](https://huggingface.co/sberbank-ai/ruT5-base).
Finetuned on [
russe_detox_2022](https://github.com/skoltech-nlp/russe_detox_2022) train to tox... |
fujuta/DialoGPT-medium-RonWeasley | c3fe70b1d2f4aa27ea3d98e5505a2e99c18b5f49 | 2022-05-25T00:23:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | fujuta | null | fujuta/DialoGPT-medium-RonWeasley | 184 | null | transformers | 3,727 | ---
tags:
- conversational
--- |
alenusch/mt5small-ruparaphraser | 1d8fcea52a546efa20a28147225c56840dd4b5e8 | 2021-06-23T15:05:47.000Z | [
"pytorch",
"jax",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | alenusch | null | alenusch/mt5small-ruparaphraser | 183 | null | transformers | 3,728 | Entry not found |
ghadeermobasher/BC2GM-Gene_ImbalancedBioM-ELECTRA-Base-Discriminator | 4c5e16ad0d7c77d23da99e5baa2868faeba69a09 | 2022-01-23T01:04:00.000Z | [
"pytorch",
"electra",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC2GM-Gene_ImbalancedBioM-ELECTRA-Base-Discriminator | 183 | null | transformers | 3,729 | Entry not found |
surajp/gpt2-hindi | bb760a44a89a1fada37bafaa5b68f5f791b54c93 | 2021-05-23T13:02:32.000Z | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | surajp | null | surajp/gpt2-hindi | 183 | null | transformers | 3,730 | Entry not found |
IDEA-CCNL/YuyuanQA-GPT2-3.5B | 3e50e27e3aded301abff14d19cd259b5740929fc | 2022-04-18T02:46:32.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"QA",
"medical",
"license:apache-2.0"
] | text-generation | false | IDEA-CCNL | null | IDEA-CCNL/YuyuanQA-GPT2-3.5B | 183 | null | transformers | 3,731 | ---
language:
- en
inference:
parameters:
temperature: 0.7
top_p: 0.6
max_new_tokens: 64
num_return_sequences: 3
do_sample: true
license: apache-2.0
tags:
- QA
- medical
- gpt2
widget:
- text: "Question:What should gout patients pay attention to in diet? Answer:"
example_title: "test Que... |
tezign/BERT-LSTM-based-ABSA | 30bf7f71427501ca7a5300825589f2a708843566 | 2022-07-20T10:14:35.000Z | [
"pytorch",
"BertABSAForSequenceClassification",
"text-classification",
"en",
"dataset:semeval2014",
"arxiv:2002.04815",
"transformers",
"aspect-term-sentiment-analysis",
"ATSA"
] | text-classification | false | tezign | null | tezign/BERT-LSTM-based-ABSA | 183 | null | transformers | 3,732 | ---
language: en
tags:
- aspect-term-sentiment-analysis
- pytorch
- ATSA
datasets:
- semeval2014
widget:
- text: "[CLS] The appearance is very nice, but the battery life is poor. [SEP] appearance [SEP] "
---
# Note
`Aspect term sentiment analysis`
BERT LSTM based baseline, based on https://github.com/avinashsai/BERT... |
kakife3586/Eka.mini | c9ae92c81c76361f42058960d4f6a3dfbf6284fd | 2022-07-15T08:21:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | kakife3586 | null | kakife3586/Eka.mini | 183 | null | transformers | 3,733 | Entry not found |
hfl/chinese-legal-electra-base-generator | c1f0ad95b487f1ed588a5e111095a16e01333b95 | 2021-10-30T23:52:25.000Z | [
"pytorch",
"tf",
"electra",
"pretraining",
"zh",
"arxiv:2004.13922",
"transformers",
"license:apache-2.0"
] | null | false | hfl | null | hfl/chinese-legal-electra-base-generator | 182 | 2 | transformers | 3,734 | ---
language:
- zh
license: "apache-2.0"
---
# This model is specifically designed for legal domain.
## Chinese ELECTRA
Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively competitive performance compared to BERT and its variants.
For fur... |
veroman/TourBERT | 81901413624c13f4867b0c16c1fc4f9bb4ca67ea | 2022-01-13T20:38:31.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | veroman | null | veroman/TourBERT | 182 | null | transformers | 3,735 | Entry not found |
Jenwvwmabskvwh/DialoGPT-small-josh444 | 706a7ca7d7dc6c991e8672b6d4cdfa85cb0e316f | 2022-07-25T09:19:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Jenwvwmabskvwh | null | Jenwvwmabskvwh/DialoGPT-small-josh444 | 182 | 0 | transformers | 3,736 | ---
tags:
- conversational
---
# Josh DialoGPT Model |
cometrain/neurotitle-rugpt3-small | c97068c6016e5162e6cb15b1c5ea8dbf828f50bc | 2021-12-07T07:54:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"en",
"dataset:All-NeurIPS-Papers-Scraper",
"transformers",
"Cometrain AutoCode",
"Cometrain AlphaML"
] | text-generation | false | cometrain | null | cometrain/neurotitle-rugpt3-small | 181 | 1 | transformers | 3,737 | ---
language:
- ru
- en
tags:
- Cometrain AutoCode
- Cometrain AlphaML
datasets:
- All-NeurIPS-Papers-Scraper
widget:
- text: "NIPSE:"
example_title: "NIPS"
- text: "Learning CNN"
example_title: "Learning CNN"
- text: "ONNX:"
example_title: "ONNX"
- text: "BERT:"
example_title: "BERT"
inference:
parameter... |
M-FAC/bert-mini-finetuned-sst2 | 431f327124d470b035264800d0eaabcc667979e2 | 2021-12-13T08:13:26.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2107.03356",
"transformers"
] | text-classification | false | M-FAC | null | M-FAC/bert-mini-finetuned-sst2 | 181 | null | transformers | 3,738 | # BERT-mini model finetuned with M-FAC
This model is finetuned on SST-2 dataset with state-of-the-art second-order optimizer M-FAC.
Check NeurIPS 2021 paper for more details on M-FAC: [https://arxiv.org/pdf/2107.03356.pdf](https://arxiv.org/pdf/2107.03356.pdf).
## Finetuning setup
For fair comparison against default... |
cambridgeltl/trans-encoder-bi-simcse-roberta-large | a1ac9780910ff21dfa0c90296b8e221ead1f55a7 | 2021-10-18T13:29:43.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"arxiv:2109.13059",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/trans-encoder-bi-simcse-roberta-large | 181 | null | transformers | 3,739 | ---
language: en
tags:
- sentence-embeddings
- sentence-similarity
- dual-encoder
### cambridgeltl/trans-encoder-bi-simcse-roberta-large
An unsupervised sentence encoder (bi-encoder) proposed by [Liu et al. (2021)](https://arxiv.org/pdf/2109.13059.pdf). The model is trained with unlabelled sentence pairs sampled from... |
mrm8488/GPT-2-finetuned-common_gen | 987b8a56a1954c7b785f52c4940f9487fa42049f | 2021-05-23T10:12:07.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:common_gen",
"transformers"
] | text-generation | false | mrm8488 | null | mrm8488/GPT-2-finetuned-common_gen | 181 | 2 | transformers | 3,740 | ---
language: en
datasets:
- common_gen
widget:
- text: "<|endoftext|> apple, tree, pick:"
---
# GPT-2 fine-tuned on CommonGen
[GPT-2](https://huggingface.co/gpt2) fine-tuned on [CommonGen](https://inklab.usc.edu/CommonGen/index.html) for *Generative Commonsense Reasoning*.
## Details of GPT-2
GPT-2 is a transforme... |
mrm8488/spanish-gpt2 | c53565b371d3d52620c5ef24800124763ecb4b54 | 2021-07-16T11:02:28.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"es",
"dataset:large_spanish_corpus",
"transformers",
"GPT-2",
"license:mit"
] | text-generation | false | mrm8488 | null | mrm8488/spanish-gpt2 | 181 | 5 | transformers | 3,741 | ---
language: es
tags:
- GPT-2
datasets:
- large_spanish_corpus
widgets:
- text: "Érase un vez un"
license: mit
---
# Spanish GPT-2 trained on [large_spanish_corpus](https://huggingface.co/datasets/viewer/?dataset=large_spanish_corpus)
This is a Spanish GPT-2 model trained from scratch on the [large_spanish_corpus]... |
lewiswu1209/Vicky | 8b1dcb0d9fcbddbaa3cc9bec0ba57596b7f954e3 | 2022-07-17T10:01:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:mit"
] | text-generation | false | lewiswu1209 | null | lewiswu1209/Vicky | 181 | null | transformers | 3,742 | ---
license: mit
---
# Vicky
Vicky是引用自开源项目GPT2-chitchat的作者分享的[50w闲聊语料训练的模型](https://github.com/yangjianxin1/GPT2-chitchat/#model_share)
我修改了vocab.txt, 新增了`[NAME][NICK][GENDER][YEAROFBIRTH][MONTHOFBIRTH][DAYOFBIRTH][ZODIAC][AGE]`几个token，然后搞了些类似
```
你是谁？
我是[NAME]。
你叫什么？
我叫[NAME]。
你多大啦？
我[AGE]岁了。
```
的语料。
但是好像被我把脑子训瓦特... |
Nakul24/AD_ChatBot | 143b0aba3a0b91823cde5725f99040370122bbda | 2022-07-17T08:51:31.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Nakul24 | null | Nakul24/AD_ChatBot | 181 | null | transformers | 3,743 | ---
tags:
- conversational
---
# Hello |
Helsinki-NLP/opus-mt-ilo-en | cb5fb67823253ca21e643f7ef6636bc6cbdaab34 | 2020-08-21T14:42:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ilo",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ilo-en | 180 | null | transformers | 3,744 | ---
language:
- ilo
- en
tags:
- translation
license: apache-2.0
---
### ilo-eng
* source group: Iloko
* target group: English
* OPUS readme: [ilo-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ilo-eng/README.md)
* model: transformer-align
* source language(s): ilo
* target language... |
keepitreal/vietnamese-sbert | a9467ef2ef47caa6448edeabfd8e5e5ce0fa2a23 | 2022-02-19T08:01:34.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers",
"vietnamese"
] | sentence-similarity | false | keepitreal | null | keepitreal/vietnamese-sbert | 180 | 2 | sentence-transformers | 3,745 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- vietnamese
---
# {vietnamese-sbert}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for... |
vasudevgupta/mbart-iitb-hin-eng | 34cac4c29ccb030fd43a1d678d3854a940848062 | 2021-05-12T03:35:21.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"dataset:pib",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vasudevgupta | null | vasudevgupta/mbart-iitb-hin-eng | 180 | 1 | transformers | 3,746 | ---
datasets: pib
widget:
- text: "नमस्ते! मैं वासुदेव गुप्ता हूं"
---
mBART (a pre-trained model by Facebook) is pre-trained to de-noise multiple languages simultaneously with BART objective.
Checkpoint available in this repository is obtained after fine-tuning `facebook/mbart-large-cc25` on 0.5 M samples from IIT-... |
l3cube-pune/hing-bert-lid | c14d7b0a643791e4b1f3c0fd3b0aa3496602908e | 2022-06-26T15:08:11.000Z | [
"pytorch",
"bert",
"token-classification",
"hi",
"en",
"dataset:L3Cube-HingCorpus",
"dataset:L3Cube-HingLID",
"arxiv:2204.08398",
"transformers",
"codemix",
"license:cc-by-4.0",
"autotrain_compatible"
] | token-classification | false | l3cube-pune | null | l3cube-pune/hing-bert-lid | 180 | 1 | transformers | 3,747 | ---
license: cc-by-4.0
language:
- hi
- en
tags:
- hi
- en
- codemix
datasets:
- L3Cube-HingCorpus
- L3Cube-HingLID
---
## HingBERT-LID
HingBERT-LID is a Hindi-English code-mixed language identification BERT model. It is a HingBERT model fine-tuned on L3Cube-HingLID dataset.
<br>
[dataset link] (https://github.com/l3... |
csebuetnlp/mT5_m2o_arabic_crossSum | e5c5b34c1d0853f4f8015e24223dda7c1c856787 | 2022-04-22T15:05:09.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"am",
"ar",
"az",
"bn",
"my",
"zh",
"en",
"fr",
"gu",
"ha",
"hi",
"ig",
"id",
"ja",
"rn",
"ko",
"ky",
"mr",
"ne",
"om",
"ps",
"fa",
"pcm",
"pt",
"pa",
"ru",
"gd",
"sr",
"si",
"so",
"es",
"sw",
"ta",
"te... | summarization | false | csebuetnlp | null | csebuetnlp/mT5_m2o_arabic_crossSum | 180 | null | transformers | 3,748 | ---
tags:
- summarization
- mT5
language:
- am
- ar
- az
- bn
- my
- zh
- en
- fr
- gu
- ha
- hi
- ig
- id
- ja
- rn
- ko
- ky
- mr
- ne
- om
- ps
- fa
- pcm
- pt
- pa
- ru
- gd
- sr
- si
- so
- es
- sw
- ta
- te
- th
- ti
- tr
- uk
- ur
- uz
- vi
- cy
- yo
licenses:
- cc-by-nc-sa-4.0
widget:
- text: "Videos that say a... |
skytnt/gpt2-japanese-lyric-medium | a63ce41c4ccc273fc55f3d5a7358aa0bb13f30c5 | 2022-07-09T01:23:58.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"ja",
"transformers",
"japanese",
"lm",
"nlp",
"license:mit"
] | text-generation | false | skytnt | null | skytnt/gpt2-japanese-lyric-medium | 180 | null | transformers | 3,749 | ---
language: ja
tags:
- ja
- japanese
- gpt2
- text-generation
- lm
- nlp
license: mit
widget:
- text: "<s>桜[CLS]"
---
# Japanese GPT2 Lyric Model
## Model description
The model is used to generate Japanese lyrics.
## How to use
```python
import torch
from transformers import T5Tokenizer, GPT2LMHeadModel
device ... |
tinkoff-ai/ruDialoGPT-medium | 0b547e7cb5503ac46c1b4f89600d1d7177e740e2 | 2022-07-19T20:27:25.000Z | [
"pytorch",
"gpt2",
"ru",
"arxiv:2001.09977",
"transformers",
"conversational",
"license:mit",
"text-generation"
] | text-generation | false | tinkoff-ai | null | tinkoff-ai/ruDialoGPT-medium | 180 | null | transformers | 3,750 | ---
license: mit
pipeline_tag: text-generation
widget:
- text: "@@ПЕРВЫЙ@@ привет @@ВТОРОЙ@@ привет @@ПЕРВЫЙ@@ как дела? @@ВТОРОЙ@@"
example_title: "how r u"
- text: "@@ПЕРВЫЙ@@ что ты делал на выходных? @@ВТОРОЙ@@"
example_title: "wyd"
language:
- ru
tags:
- conversational
---
This generation model is based on [sb... |
Rifky/Indobert-QA | 9c00be563bd5370d983746480fa1545ef9cc08ee | 2021-10-08T12:04:06.000Z | [
"pytorch",
"bert",
"question-answering",
"id",
"dataset:220M words (IndoWiki, IndoWC, News)",
"dataset:Squad 2.0 (Indonesian translated)",
"transformers",
"indobert",
"indolem",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | Rifky | null | Rifky/Indobert-QA | 179 | 2 | transformers | 3,751 | ---
language: id
tags:
- indobert
- indolem
license: apache-2.0
datasets:
- 220M words (IndoWiki, IndoWC, News)
- Squad 2.0 (Indonesian translated)
widget:
- text: kapan pangeran diponegoro lahir?
context: Pangeran Harya Dipanegara (atau biasa dikenal dengan nama Pangeran Diponegoro,
lahir di Ngayogyakarta Hadini... |
SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune | 9f4f6210a883876e7e7a41f884f12d374ad489ea | 2021-06-23T06:45:18.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_large_code_documentation_generation_java_multitask_finetune | 179 | null | transformers | 3,752 | ---
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 large model architecture... |
huggingface-course/marian-finetuned-kde4-en-to-fr | b62de7715951556628f8d9c632f95458e98c2010 | 2021-11-11T17:45:32.000Z | [
"pytorch",
"tf",
"tensorboard",
"marian",
"text2text-generation",
"dataset:kde4",
"transformers",
"translation",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | translation | false | huggingface-course | null | huggingface-course/marian-finetuned-kde4-en-to-fr | 179 | null | transformers | 3,753 | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
datasets:
- kde4
metrics:
- bleu
model-index:
- name: test-marian-finetuned-kde4-en-to-fr
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: kde4
type: kde4
arg... |
sismetanin/xlm_roberta_large-ru-sentiment-rusentiment | 30e2af4eba27e79d741688ff4e4c5a607dac93f2 | 2021-02-25T23:57:27.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ru",
"transformers",
"sentiment analysis",
"Russian"
] | text-classification | false | sismetanin | null | sismetanin/xlm_roberta_large-ru-sentiment-rusentiment | 179 | 1 | transformers | 3,754 | ---
language:
- ru
tags:
- sentiment analysis
- Russian
---
## XML-RoBERTa-Large-ru-sentiment-RuSentiment
XML-RoBERTa-Large-ru-sentiment-RuSentiment is a [XML-RoBERTa-Large](https://huggingface.co/xlm-roberta-large) model fine-tuned on [RuSentiment dataset](https://github.com/text-machine-lab/rusentiment) of general... |
textattack/albert-base-v2-SST-2 | 96d7dedb92b3679c4f1ae69e7e77440d058d8602 | 2020-07-06T16:32:15.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/albert-base-v2-SST-2 | 179 | null | transformers | 3,755 | ## TextAttack Model Card
This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 32, a learning
rate of 3e-05, and a maximum sequence length of 64.
Since this was a classif... |
jirmauritz/bert-multilingual-emoji | 4ef7879bcac5b81f4a941af9638b088e32ccb6e4 | 2021-06-28T13:43:26.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"multilingual",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | jirmauritz | null | jirmauritz/bert-multilingual-emoji | 178 | null | transformers | 3,756 | ---
language: multilingual
license: apache-2.0
datasets:
- wikipedia
---
# BERT multilingual base model (cased)
Pretrained model on the top 104 languages with the largest Wikipedia using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released ... |
microsoft/beit-large-patch16-224 | 0bd443cfdfa82333978cac2253da417b33ff5018 | 2022-01-28T10:19:16.000Z | [
"pytorch",
"jax",
"beit",
"image-classification",
"dataset:imagenet",
"dataset:imagenet-21k",
"arxiv:2106.08254",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/beit-large-patch16-224 | 178 | null | transformers | 3,757 | ---
license: apache-2.0
tags:
- image-classification
- vision
datasets:
- imagenet
- imagenet-21k
---
# BEiT (large-sized model, fine-tuned on ImageNet-1k)
BEiT model pre-trained in a self-supervised fashion on ImageNet-21k (14 million images, 21,841 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1... |
pedrobaiainin/DialoGPT-small-harrypotter | d815a8618b4759f47704020670997f3261ce3efe | 2022-05-12T22:18:37.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | pedrobaiainin | null | pedrobaiainin/DialoGPT-small-harrypotter | 178 | null | transformers | 3,758 | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model |
cambridgeltl/trans-encoder-cross-simcse-roberta-base | 7e07c5daa82e8407d2fcb435a7360ea0033b1990 | 2021-11-26T18:22:19.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | cambridgeltl | null | cambridgeltl/trans-encoder-cross-simcse-roberta-base | 177 | null | transformers | 3,759 | Entry not found |
cardiffnlp/twitter-roberta-base-2019-90m | b28ca2617bbb48f241d88bcadeafd641d4ef62a3 | 2022-02-09T11:11:16.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-2019-90m | 177 | null | transformers | 3,760 | # Twitter 2021 90M (RoBERTa-base)
This is a RoBERTa-base model trained on 90M tweets until the end of 2019.
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 another interface... |
lysandre/arxiv-nlp | 894a9adde21d9a3e3843e6d5aeaaf01875c7fade | 2021-05-23T08:42:23.000Z | [
"pytorch",
"jax",
"gpt2",
"transformers"
] | null | false | lysandre | null | lysandre/arxiv-nlp | 177 | null | transformers | 3,761 | # ArXiv-NLP GPT-2 checkpoint
This is a GPT-2 small checkpoint for PyTorch. It is the official `gpt2-small` fine-tuned to ArXiv paper on the computational linguistics field.
## Training data
This model was trained on a subset of ArXiv papers that were parsed from PDF to txt. The resulting data is made of 80MB of text... |
voidful/context-only-question-generator | cc10aa73ab4cc0ef15e91403b7efabdb05872c9c | 2021-12-09T12:43:26.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:unifiedQA",
"transformers",
"question",
"generation",
"seq2seq",
"autotrain_compatible"
] | text2text-generation | false | voidful | null | voidful/context-only-question-generator | 177 | 1 | transformers | 3,762 | ---
language: en
tags:
- bart
- question
- generation
- seq2seq
datasets:
- unifiedQA
metrics:
- bleu
- rouge
pipeline_tag: text2text-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author J. K. Rowling. The novels chronicle the lives of a young wizard, Harry Potter, and ... |
soleimanian/financial-roberta-large-sentiment | acdaa9e81863b9c0b2b44fa1083274effe237817 | 2022-05-31T16:52:46.000Z | [
"pytorch",
"roberta",
"text-classification",
"English",
"transformers",
"Sentiment",
"RoBERTa",
"Financial Statements",
"Accounting",
"Finance",
"Business",
"ESG",
"CSR Reports",
"Financial News",
"Earnings Call Transcripts",
"Sustainability",
"Corporate governance",
"license:apach... | text-classification | false | soleimanian | null | soleimanian/financial-roberta-large-sentiment | 177 | 1 | transformers | 3,763 | ---
license: apache-2.0
language:
- English
tags:
- text-classification
- Sentiment
- RoBERTa
- Financial Statements
- Accounting
- Finance
- Business
- ESG
- CSR Reports
- Financial News
- Earnings Call Transcripts
- Sustainability
- Corporate governance
---
<!DOCTYPE html>
<html>
<body>
<h1><b>Financial-RoBERTa</... |
soProf1998/DialoGPT-medium-chattyrick | 919992ba164ab1ca64f71c5a9908f75cf239b852 | 2022-06-26T10:49:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:mit"
] | conversational | false | soProf1998 | null | soProf1998/DialoGPT-medium-chattyrick | 177 | 1 | transformers | 3,764 | ---
thumbnail: https://raw.githubusercontent.com/RuolinZheng08/twewy-discord-chatbot/main/gif-demo/icon.png
tags:
- conversational
license: mit
---
# DialoGPT Trained on the Speech of Rick from [The Show Rick & Morty]
This is an instance of [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-me... |
Evelyn18/distilbert-base-uncased-becas-1 | 4b3346df8a5d11bef9e175d7c53e634a19959506 | 2022-07-02T02:44:08.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"dataset:becasv2",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | Evelyn18 | null | Evelyn18/distilbert-base-uncased-becas-1 | 177 | null | transformers | 3,765 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- becasv2
model-index:
- name: distilbert-base-uncased-becas-1
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... |
hf-internal-testing/tiny-random-wavlm | 3cabe08e16f230d3c4fb7d5ac3e1207349c6751f | 2022-01-26T12:49:55.000Z | [
"pytorch",
"wavlm",
"audio-classification",
"transformers"
] | audio-classification | false | hf-internal-testing | null | hf-internal-testing/tiny-random-wavlm | 176 | null | transformers | 3,766 | Entry not found |
huggingtweets/drilbot_neo | cf026e12b01e82c9fafb1d342c352a0572a56279 | 2022-06-10T08:39:44.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/drilbot_neo | 176 | null | transformers | 3,767 | ---
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... |
phueb/BabyBERTa-1 | 86e225d8c3c3bda86cf6bd587ba1f3a660d993be | 2022-01-18T14:44:02.000Z | [
"pytorch",
"roberta",
"fill-mask",
"en",
"dataset:CHILDES",
"transformers",
"BabyBERTa",
"autotrain_compatible"
] | fill-mask | false | phueb | null | phueb/BabyBERTa-1 | 176 | null | transformers | 3,768 | ---
language: en
tags:
- BabyBERTa
datasets:
- CHILDES
widget:
- text: "Look here. What is that <mask> ?"
- text: "Do you like your <mask> ?"
---
## BabyBERTA
### Overview
BabyBERTa is a light-weight version of RoBERTa trained on 5M words of American-English child-directed input.
It is intended for language acquisit... |
WENGSYX/CirBERTa-Chinese-Base | 8e99626274d926a909165b08444ac3011bf85b67 | 2022-04-14T14:27:04.000Z | [
"pytorch",
"deberta-v2",
"transformers"
] | null | false | WENGSYX | null | WENGSYX/CirBERTa-Chinese-Base | 176 | 3 | transformers | 3,769 | # CirBERTa
### Apply the Circular to the Pretraining Model
| 预训练模型 | 学习率 | batchsize | 设备 | 语料库 | 时间 | 优化器 |
| --------------------- | ------ | --------- | ------ | ------ | ---- | ------ |
| CirBERTa-Chinese-Base | 1e-5 | 256 | 10张3090+3张A100 | 200G | 2月 | AdamW |
使用通用语料（WuDao 200G) 进行无监督预... |
CenIA/distillbert-base-spanish-uncased-finetuned-ner | 17496d7bf9d359c720cfd2913e9dd2816941adf2 | 2022-01-06T19:42:07.000Z | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | CenIA | null | CenIA/distillbert-base-spanish-uncased-finetuned-ner | 175 | null | transformers | 3,770 | Entry not found |
m3hrdadfi/wav2vec2-large-xlsr-icelandic | b69b134c43165dadb01ba83cfcadd84ad678938a | 2021-11-04T15:22:07.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"is",
"dataset:malromur",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | m3hrdadfi | null | m3hrdadfi/wav2vec2-large-xlsr-icelandic | 175 | null | transformers | 3,771 | ---
language: is
datasets:
- malromur
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
widget:
- example_title: Malromur sample 1608
src: https://huggingface.co/m3hrdadfi/wav2vec2-large-xlsr-icelandic/resolve/main/sample1608.flac
- example_title: Malromur sample 3860
... |
ml6team/mbart-large-cc25-cnn-dailymail-xsum-nl | c64279de2b23d3b081cd4c44edf45dc090d02a03 | 2022-05-16T11:41:07.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"nl",
"dataset:ml6team/cnn_dailymail_nl",
"dataset:ml6team/xsum_nl",
"transformers",
"bart",
"summarization",
"autotrain_compatible"
] | summarization | false | ml6team | null | ml6team/mbart-large-cc25-cnn-dailymail-xsum-nl | 175 | 2 | transformers | 3,772 | ---
language:
- nl
tags:
- mbart
- bart
- summarization
datasets:
- ml6team/cnn_dailymail_nl
- ml6team/xsum_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... |
moussaKam/barthez-sentiment-classification | adba67e0571033563349a3758a0459d44653331c | 2021-11-15T13:02:33.000Z | [
"pytorch",
"mbart",
"text-classification",
"fr",
"arxiv:2010.12321",
"transformers",
"bart",
"license:apache-2.0"
] | text-classification | false | moussaKam | null | moussaKam/barthez-sentiment-classification | 175 | 1 | transformers | 3,773 | ---
tags:
- text-classification
- bart
language:
- fr
license: apache-2.0
widget:
- text: Barthez est le meilleur gardien du monde.
---
### Barthez model finetuned on opinion classification task.
paper: https://arxiv.org/abs/2010.12321 \
github: https://github.com/moussaKam/BARThez
```
@article{eddine2020barthez,... |
StanfordAIMI/RadBERT | ce3f7a29afd4f0c5c88c89672c52a8dd7cbdbb5c | 2022-05-07T23:22:33.000Z | [
"pytorch",
"bert",
"fill-mask",
"en",
"dataset:wikipedia",
"dataset:bookscorpus",
"dataset:pubmed",
"dataset:radreports",
"transformers",
"biobert",
"radbert",
"language-model",
"uncased",
"radiology",
"biomedical",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | StanfordAIMI | null | StanfordAIMI/RadBERT | 175 | 5 | transformers | 3,774 | ---
widget:
- text: "low lung volumes, [MASK] pulmonary vascularity."
tags:
- fill-mask
- pytorch
- transformers
- bert
- biobert
- radbert
- language-model
- uncased
- radiology
- biomedical
datasets:
- wikipedia
- bookscorpus
- pubmed
- radreports
language:
- en
license: mit
---
RadBERT was continuously pre-trai... |
EMBO/BioMegatron345mCased | 3b82e192316436e689c58d24bb55ef6223953b64 | 2022-05-31T13:24:48.000Z | [
"pytorch",
"megatron-bert",
"english",
"arxiv:2010.06060",
"transformers",
"language model",
"license:cc-by-4.0"
] | null | false | EMBO | null | EMBO/BioMegatron345mCased | 175 | null | transformers | 3,775 | ---
license: cc-by-4.0
language:
- english
thumbnail:
tags:
- language model
---
!---
# ##############################################################################################
#
# This model has been uploaded to HuggingFace by https://huggingface.co/drAbreu
# The model is based on the NVIDIA checkpoint locat... |
Bhuvana/t5-base-spellchecker | 02a2e8005ea4ad2c6ad3f1d59c92f4db804989eb | 2022-01-04T12:46:55.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Bhuvana | null | Bhuvana/t5-base-spellchecker | 174 | null | transformers | 3,776 | ---
widget:
- text: "christmas is celbrated on decembr 25 evry ear"
---
# Spell checker using T5 base transformer
A simple spell checker built using T5-Base transformer. To use this model
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Bhuvana/t5-base-s... |
Geotrend/distilbert-base-zh-cased | c656a076c3ed58dfb48db7befc555feed5c4dc82 | 2021-08-16T13:15:12.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"zh",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/distilbert-base-zh-cased | 174 | null | transformers | 3,777 | ---
language: zh
datasets: wikipedia
license: apache-2.0
---
# distilbert-base-zh-cased
We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.
Our versions give exactly the same representations pro... |
Guscode/DKbert-hatespeech-detection | edbbde93f7c0eced542a84ca47ab9dbb74b58605 | 2021-09-22T07:55:16.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"da",
"dataset:DKHate - OffensEval2020",
"transformers",
"Hatespeech",
"Danish",
"BERT",
"license:mit"
] | text-classification | false | Guscode | null | Guscode/DKbert-hatespeech-detection | 174 | 1 | transformers | 3,778 | ---
language:
- da
tags:
- Hatespeech
- Danish
- BERT
license: mit
datasets:
- DKHate - OffensEval2020
Classes:
- Hateful
- Not Hateful
---
# DKbert-hatespeech-classification
Use this model to detect hatespeech in Danish. For details, guide and command line tool see [DK hate github](https://github.com/Guscode/DKbe... |
jonatasgrosman/wav2vec2-xls-r-1b-french | 1ad5b48188ef40418935fff76f992178217941c8 | 2022-07-27T23:39:10.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | jonatasgrosman | null | jonatasgrosman/wav2vec2-xls-r-1b-french | 174 | 4 | transformers | 3,779 | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- fr
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R Wav2Vec2 French by Jonatas Grosman
results:
- task:
name: Automatic Speec... |
Inari/deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli | ca16637efa5f33a76416b864af7594d5221ed025 | 2022-04-25T13:37:15.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"dataset:snli-1.0",
"dataset:multi-nli-1.0",
"dataset:nli-fever",
"dataset:anli-v1.0",
"transformers"
] | text-classification | false | Inari | null | Inari/deberta-v3-large-snli_mnli_fever_anli_R1_R2_R3-nli | 174 | null | transformers | 3,780 | ---
language:
- en
tags:
- text-classification
metrics:
- accuracy
datasets:
- snli-1.0
- multi-nli-1.0
- nli-fever
- anli-v1.0
widget:
- text: "British mountaineer Alison Hargreaves becomes the first woman to climb Mount Everest alone and without oxygen tanks. [SEP] Alison is a female."
- text: "Mr Lopez Obrador has ... |
reso/DialoGPT-medium-v3ga | d551a467455d619f3414c7e6ffed976a9d75bc86 | 2022-07-04T19:39:14.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:mit"
] | conversational | false | reso | null | reso/DialoGPT-medium-v3ga | 174 | null | transformers | 3,781 | ---
thumbnail: https://raw.githubusercontent.com/RuolinZheng08/twewy-discord-chatbot/main/gif-demo/icon.png
tags:
- conversational
license: mit
---
# DialoGPT Trained on the Speech of a Game Character
This is an instance of [microsoft/DialoGPT-medium](https://huggingface.co/microsoft/DialoGPT-medium) trained on ... |
Helsinki-NLP/opus-mt-mos-en | 31c4672f10b25f8f252e5df197e889866e9d0799 | 2021-09-10T13:58:16.000Z | [
"pytorch",
"marian",
"text2text-generation",
"mos",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-mos-en | 173 | null | transformers | 3,782 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-mos-en
* source languages: mos
* target languages: en
* OPUS readme: [mos-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/mos-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Nhut/wav2vec2-large-xlsr-french | b20d283faaa21db8638c577f1f9d9ee6d2ebd157 | 2021-07-05T16:25:03.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Nhut | null | Nhut/wav2vec2-large-xlsr-french | 173 | 1 | transformers | 3,783 | ---
language: fr
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: wav2vec2-large-xlsr-53-French by Nhut DOAN NGUYEN
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
... |
asapp/sew-d-tiny-100k-ft-ls100h | 443b29018d4aa5af937b2d1ee75d965d63ddf595 | 2022-05-24T13:10:21.000Z | [
"pytorch",
"sew-d",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2109.06870",
"transformers",
"audio",
"speech",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | asapp | null | asapp/sew-d-tiny-100k-ft-ls100h | 173 | 1 | transformers | 3,784 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- speech
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.hug... |
cosmoquester/bart-ko-mini | 0dd647b1a8511ed034345004bb0f825a36b10b89 | 2021-08-28T04:59:29.000Z | [
"pytorch",
"tf",
"bart",
"text2text-generation",
"ko",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | cosmoquester | null | cosmoquester/bart-ko-mini | 173 | null | transformers | 3,785 | ---
language: ko
---
# Pretrained BART in Korean
This is pretrained BART model with multiple Korean Datasets.
I used multiple datasets for generalizing the model for both colloquial and written texts.
The training is supported by [TPU Research Cloud](https://sites.research.google/trc/) program.
The script which is... |
dhpollack/distilbert-dummy-sentiment | 459f7eb8f9f7e9f0090d37b04dc46fb3a5c987d7 | 2021-03-23T17:40:32.000Z | [
"pytorch",
"distilbert",
"text-classification",
"multilingual",
"en",
"transformers",
"sentiment-analysis",
"testing",
"unit tests"
] | text-classification | false | dhpollack | null | dhpollack/distilbert-dummy-sentiment | 173 | null | transformers | 3,786 | ---
language:
- "multilingual"
- "en"
tags:
- "sentiment-analysis"
- "testing"
- "unit tests"
---
# DistilBert Dummy Sentiment Model
## Purpose
This is a dummy model that can be used for testing the transformers `pipeline` with the task `sentiment-analysis`. It should always give random results (i.e. `{"label": "neg... |
kornosk/bert-election2020-twitter-stance-trump-KE-MLM | 94546163d364120dc06da461b0f154ee69df6683 | 2022-05-02T22:58:49.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"transformers",
"twitter",
"stance-detection",
"election2020",
"politics",
"license:gpl-3.0"
] | text-classification | false | kornosk | null | kornosk/bert-election2020-twitter-stance-trump-KE-MLM | 173 | 1 | transformers | 3,787 | ---
language: "en"
tags:
- twitter
- stance-detection
- election2020
- politics
license: "gpl-3.0"
---
# Pre-trained BERT on Twitter US Election 2020 for Stance Detection towards Donald Trump (KE-MLM)
Pre-trained weights for **KE-MLM model** in [Knowledge Enhance Masked Language Model for Stance Detection](https://ww... |
pertschuk/albert-intent-model-v3 | a2cd0d5365e563c569eb4c0314caf7977312dcf2 | 2020-04-24T16:05:05.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | pertschuk | null | pertschuk/albert-intent-model-v3 | 173 | null | transformers | 3,788 | Entry not found |
yosemite/autonlp-imdb-sentiment-analysis-english-470512388 | 048ac53e79fb2eddd3a04b74f0981df4f414d013 | 2022-01-04T17:34:50.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:yosemite/autonlp-data-imdb-sentiment-analysis-english",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | yosemite | null | yosemite/autonlp-imdb-sentiment-analysis-english-470512388 | 173 | null | transformers | 3,789 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- yosemite/autonlp-data-imdb-sentiment-analysis-english
co2_eq_emissions: 256.38650494338367
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 470512388
- CO2 Emissions (in grams): 256.38650494338367
## Val... |
Gunulhona/tbnlimodel_v1 | 94a6673d4d2d98dc6c3a553052e74b2c232a50b1 | 2022-07-30T08:57:14.000Z | [
"pytorch",
"bart",
"feature-extraction",
"transformers"
] | feature-extraction | false | Gunulhona | null | Gunulhona/tbnlimodel_v1 | 173 | null | transformers | 3,790 | Entry not found |
Davlan/bert-base-multilingual-cased-finetuned-swahili | 24be68534e4b27a44f1d4791fc1c39bc014863c4 | 2022-06-27T11:50:13.000Z | [
"pytorch",
"tf",
"bert",
"fill-mask",
"ha",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Davlan | null | Davlan/bert-base-multilingual-cased-finetuned-swahili | 172 | 1 | transformers | 3,791 | Hugging Face's logo
---
language: ha
datasets:
---
# bert-base-multilingual-cased-finetuned-swahili
## Model description
**bert-base-multilingual-cased-finetuned-swahili** is a **Swahili BERT** model obtained by fine-tuning **bert-base-multilingual-cased** model on Swahili language texts. It provides **better perform... |
JP040/bert-german-sentiment-twitter | 491f7278ac030c56601b1021c6fc68454d57b3ca | 2021-05-18T21:14:38.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | JP040 | null | JP040/bert-german-sentiment-twitter | 172 | null | transformers | 3,792 | Entry not found |
Rostlab/prot_bert_bfd_ss3 | 058aa452532c34f803dca9b89c80a85417e59c17 | 2021-05-18T22:11:42.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Rostlab | null | Rostlab/prot_bert_bfd_ss3 | 172 | 1 | transformers | 3,793 | Entry not found |
Wikidepia/marian-nmt-enid | 1e36963d83e7c41b45972443158537f746e40729 | 2021-06-03T07:27:50.000Z | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Wikidepia | null | Wikidepia/marian-nmt-enid | 172 | null | transformers | 3,794 | # NMT Model for English-Indonesian
|
alenusch/rugpt2-paraphraser | 05d219ffa2b85b62f73f36037713299ee56de09c | 2021-05-21T12:47:57.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | alenusch | null | alenusch/rugpt2-paraphraser | 172 | null | transformers | 3,795 | Entry not found |
brandon25/deberta-base-finetuned-ner | 3ec3cbb582c8d490f9a7555ec7f6d8f2e24961a3 | 2021-10-12T08:05:37.000Z | [
"pytorch",
"tensorboard",
"deberta",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | brandon25 | null | brandon25/deberta-base-finetuned-ner | 172 | 1 | transformers | 3,796 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-base-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: ... |
dmitry-vorobiev/rubert_ria_headlines | 9fda809a2528837e2d142439e52c78305a921e28 | 2021-09-22T08:20:24.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"ru",
"transformers",
"summarization",
"bert",
"rubert",
"license:mit",
"autotrain_compatible"
] | summarization | false | dmitry-vorobiev | null | dmitry-vorobiev/rubert_ria_headlines | 172 | null | transformers | 3,797 | ---
language:
- ru
tags:
- summarization
- bert
- rubert
license: mit
---
# rubert_ria_headlines
## Description
*bert2bert* model, initialized with the `DeepPavlov/rubert-base-cased` pretrained weights and
fine-tuned on the first 99% of ["Rossiya Segodnya" news dataset](https://github.com/RossiyaSegodnya/ria_news... |
facebook/vit-mae-huge | 5e0e60b29318a30e9ed13e27cb56d28071704980 | 2022-03-29T16:39:28.000Z | [
"pytorch",
"tf",
"vit_mae",
"pretraining",
"dataset:imagenet-1k",
"arxiv:2111.06377",
"transformers",
"vision",
"license:apache-2.0"
] | null | false | facebook | null | facebook/vit-mae-huge | 172 | 1 | transformers | 3,798 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet-1k
---
# Vision Transformer (huge-sized model) pre-trained with MAE
Vision Transformer (ViT) model pre-trained using the MAE method. It was introduced in the paper [Masked Autoencoders Are Scalable Vision Learners](https://arxiv.org/abs/2111.06377) by Kaimin... |
huggingartists/eminem | ead4f2b57f8b9c818e49e5df460593dd8c0ec318 | 2022-07-14T16:45:19.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/eminem",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/eminem | 172 | null | transformers | 3,799 | ---
language: en
datasets:
- huggingartists/eminem
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; height:92... |
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