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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
kingabzpro/Helsinki-NLP-opus-yor-mul-en | c4b80c5880959550552c8e2c9b639df1fe5bb10c | 2021-08-03T08:43:00.000Z | [
"pytorch",
"marian",
"text2text-generation",
"Yorùbá",
"dataset:AI4D-Africa - Yorùbá Machine Translation Challenge",
"transformers",
"text",
"machine-translation",
"language-translation",
"seq2seq",
"helsinki-nlp",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | kingabzpro | null | kingabzpro/Helsinki-NLP-opus-yor-mul-en | 12 | 1 | transformers | 10,600 | ---
language: Yorùbá
datasets:
- AI4D-Africa - Yorùbá Machine Translation Challenge
tags:
- text
- machine-translation
- language-translation
- seq2seq
- helsinki-nlp
license: apache-2.0
metrics:
- ROUGE
---
## Predicting English Translation
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# Loa... |
kingabzpro/wav2vec2-60-Urdu-V8 | 26321cf95b2813b91fcb41ea5b0107d1288dafc5 | 2022-03-24T11:55:52.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"ur",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"robust-speech-event",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | kingabzpro | null | kingabzpro/wav2vec2-60-Urdu-V8 | 12 | 1 | transformers | 10,601 | ---
language:
- ur
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-urdu-V8-Abid
results:
- task:
type: automatic-speech-recognition
name: Speech Recognit... |
l3cube-pune/hate-bert-hasoc-marathi | f7fe5eff28b6bcaeacd926f89bc100af394ac210 | 2022-06-12T12:38:26.000Z | [
"pytorch",
"tf",
"albert",
"text-classification",
"mr",
"dataset:HASOC 2021",
"arxiv:2110.12200",
"transformers",
"license:cc-by-4.0"
] | text-classification | false | l3cube-pune | null | l3cube-pune/hate-bert-hasoc-marathi | 12 | 1 | transformers | 10,602 | ---
language: mr
tags:
- albert
license: cc-by-4.0
datasets:
- HASOC 2021
widget:
- text: "I like you. </s></s> I love you."
---
## hate-bert-hasoc-marathi
hate-bert-hasoc-marathi is a binary hate speech model fine-tuned on Marathi Hasoc Hate Speech Dataset 2021.
The label mappings are 0 -> None, 1 -> Hate.
More de... |
llangnickel/long-covid-classification | d914996f532b6a7b81f375ddc665551eae5099b8 | 2022-07-04T19:28:06.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | llangnickel | null | llangnickel/long-covid-classification | 12 | null | transformers | 10,603 | ---
license: mit
---
## long-covid-classification
We fine-tuned bert-base-cased using a [manually curated dataset](https://huggingface.co/llangnickel/long-covid-classification-data) to train a Sequence Classification model able to distinguish between long COVID and non-long COVID-related documents.
## Used hyper par... |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_ep_10 | f34fe7e07a03c6016d9e1957a5beb11daf35acc6 | 2021-10-25T19:54:26.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_ep_10 | 12 | null | transformers | 10,604 | Entry not found |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_oppo | 539ca45cfe17fa403bd8e6ed55f37188337100e6 | 2021-10-26T07:55:09.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_oppo | 12 | null | transformers | 10,605 | Entry not found |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_wu_7k_grad_adam | 02a8790e1571a2aae34f04791d017da45c010939 | 2021-10-30T23:35:38.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_wu_7k_grad_adam | 12 | null | transformers | 10,606 | Entry not found |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_wu_7k_grad_adam_mask | ca63ce03489c34f3306ad7d21496823aa9a2c5c1 | 2021-10-31T20:56:51.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_wu_7k_grad_adam_mask | 12 | null | transformers | 10,607 | Entry not found |
lvwerra/gpt2-imdb-pos | 649cebcaa8604cbf6124f3d26651d9f5cc1e0e56 | 2021-05-23T08:37:41.000Z | [
"pytorch",
"gpt2",
"transformers"
] | null | false | lvwerra | null | lvwerra/gpt2-imdb-pos | 12 | null | transformers | 10,608 | # GPT2-IMDB-pos
## What is it?
A small GPT2 (`lvwerra/gpt2-imdb`) language model fine-tuned to produce positive movie reviews based the [IMDB dataset](https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews). The model is trained with rewards from a BERT sentiment classifier (`lvwerra/gpt2-imdb`) via ... |
m3hrdadfi/albert-fa-base-v2-sentiment-snappfood | e02e74a033a1f3a43b101153c666894f0d40c2df | 2020-12-26T08:49:28.000Z | [
"pytorch",
"tf",
"albert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | m3hrdadfi | null | m3hrdadfi/albert-fa-base-v2-sentiment-snappfood | 12 | null | transformers | 10,609 | ---
language: fa
license: apache-2.0
---
# ALBERT Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
[ALBERT-Persian](https://github.com/m3hrdadfi/albert-persian) is the first attempt on ALBERT for the Persian Language. The model was tra... |
malay-huggingface/t5-small-bahasa-cased | c2bdb69b07dbb25f2b329def9b776210dca6de0d | 2021-09-05T12:53:30.000Z | [
"pytorch",
"t5",
"feature-extraction",
"ms",
"transformers"
] | feature-extraction | false | malay-huggingface | null | malay-huggingface/t5-small-bahasa-cased | 12 | null | transformers | 10,610 | ---
language: ms
---
# t5-small-bahasa-cased
Pretrained T5 small language model for Malay.
## Pretraining Corpus
`t5-small-bahasa-cased` model was pretrained on multiple tasks. Below is list of tasks we trained on,
1. Language masking task on bahasa news, bahasa Wikipedia, bahasa Academia.edu, bahasa parliament a... |
manandey/wav2vec2-large-xlsr-_irish | cd3bd4e5203a049b6739790627cd843fcf5eb287 | 2022-03-25T16:53:49.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ga",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | manandey | null | manandey/wav2vec2-large-xlsr-_irish | 12 | null | transformers | 10,611 | ---
language: ga
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
- hf-asr-leaderboard
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Irish by Manan Dey
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset... |
manav/causal_qa | cd86c3a19560f9135165aa89c47230681cbcc458 | 2021-05-19T22:48:49.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | manav | null | manav/causal_qa | 12 | null | transformers | 10,612 | This a BERT-based QA model finetuned to answer causal questions. The original model this is based on can be found [here](https://huggingface.co/deepset/bert-large-uncased-whole-word-masking-squad2). Analysis of this model is associated with the work found at the following [repo](https://github.com/kstats/CausalQG). |
maroo93/practice00 | 2b1969d39fe0e579d21c0c40173e813083b22d7c | 2021-05-19T23:05:30.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | maroo93 | null | maroo93/practice00 | 12 | null | transformers | 10,613 | Entry not found |
mbeukman/xlm-roberta-base-finetuned-luganda-finetuned-ner-swahili | c5870bf17c7b54bd658e4a8c29f2bec808fc3934 | 2021-11-25T09:04:12.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"sw",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-luganda-finetuned-ner-swahili | 12 | null | transformers | 10,614 | ---
language:
- sw
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Wizara ya afya ya Tanzania imeripoti Jumatatu kuwa , watu takriban 14 zaidi wamepata maambukizi ya Covid - 19 ."
---
# xlm-roberta-base-finetuned-luganda-finetuned-ner-swahili
This is a token classification (s... |
mbeukman/xlm-roberta-base-finetuned-luo-finetuned-ner-luo | 04c29cd77e99f5753c55c7023c6500188996147a | 2021-11-25T09:04:15.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"luo",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-luo-finetuned-ner-luo | 12 | null | transformers | 10,615 | ---
language:
- luo
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Jii 2 moko jowito ngimagi ka machielo 1 to ohinyore marach mokalo e masira makoch mar apaya mane otimore e apaya mawuok Oyugis kochimo Chabera e sub county ma Rachuonyo East e County ma Homa Bay ewii odhiambo ... |
mbeukman/xlm-roberta-base-finetuned-ner-kinyarwanda | 5dba1567dba74cdf572df06b6f69b8e6cd19d665 | 2021-11-25T09:04:30.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"rw",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-ner-kinyarwanda | 12 | null | transformers | 10,616 | ---
language:
- rw
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Ambasaderi wa EU mu Rwanda , Nicola Bellomo yagize ati “ Inkunga yacu ni imwe mu nkunga yagutse yiswe # TeamEurope ."
---
# xlm-roberta-base-finetuned-ner-kinyarwanda
This is a token classification (specifical... |
mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-kinyarwanda | f5dbc45ebe3cc5a1735dd354bf45d009f6793d26 | 2021-11-25T09:04:53.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"rw",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-kinyarwanda | 12 | null | transformers | 10,617 | ---
language:
- rw
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Ambasaderi wa EU mu Rwanda , Nicola Bellomo yagize ati “ Inkunga yacu ni imwe mu nkunga yagutse yiswe # TeamEurope ."
---
# xlm-roberta-base-finetuned-swahili-finetuned-ner-kinyarwanda
This is a token classifi... |
mgreenbe/bertlet-base-uncased-for-sequence-classification | 4304bae03a8712c21a223b933283ad0c827577ac | 2021-11-20T17:23:02.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | mgreenbe | null | mgreenbe/bertlet-base-uncased-for-sequence-classification | 12 | 1 | transformers | 10,618 | ---
tags:
- generated_from_trainer
model-index:
- name: bertlet-base-uncased-for-sequence-classification
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. -->
# bertle... |
microsoft/unihanlm-base | af5693b4a92ba50b66c557868cf83ef2dfadc392 | 2021-09-22T09:00:56.000Z | [
"pytorch",
"tf",
"xlm",
"feature-extraction",
"zh",
"ja",
"dataset:Wikipedia",
"transformers",
"crosslingual",
"license:apache-2.0"
] | feature-extraction | false | microsoft | null | microsoft/unihanlm-base | 12 | 1 | transformers | 10,619 | ---
language:
- zh
- ja
tags:
- crosslingual
license: apache-2.0
datasets:
- Wikipedia
---
# Unihan LM: Coarse-to-Fine Chinese-Japanese Language Model Pretraining with the Unihan Database
## Model description
Chinese and Japanese share many characters with similar surface morphology. To better utilize the shared kno... |
microsoft/unilm-large-cased | 5818e0466f86ed8e4b2be9423afca2a6398ac2b9 | 2020-04-28T21:22:59.000Z | [
"pytorch",
"transformers"
] | null | false | microsoft | null | microsoft/unilm-large-cased | 12 | null | transformers | 10,620 | Entry not found |
midas/gupshup_e2e_gpt | 3d81322149ff40f77f9861498e390ebfdebf06c9 | 2021-11-14T02:08:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"arxiv:1910.04073",
"transformers"
] | text-generation | false | midas | null | midas/gupshup_e2e_gpt | 12 | null | transformers | 10,621 | # Gupshup
GupShup: Summarizing Open-Domain Code-Switched Conversations EMNLP 2021
Paper: [https://aclanthology.org/2021.emnlp-main.499.pdf](https://aclanthology.org/2021.emnlp-main.499.pdf)
Github: [https://github.com/midas-research/gupshup](https://github.com/midas-research/gupshup)
### Dataset
Please request for the... |
mlkorra/OGBV-gender-bert-hi-en | b494c489a82b7c0f9f44804d3d7398b1d3b33e32 | 2021-09-07T15:13:25.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | mlkorra | null | mlkorra/OGBV-gender-bert-hi-en | 12 | null | transformers | 10,622 | ## BERT Model for OGBV gendered text classification
## How to use
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mlkorra/OGBV-gender-bert-hi-en")
model = AutoModelForSequenceClassification.from_pretrained("mlkorra/OGBV-gender-bert-h... |
mobedkova/wav2vec2-large-xls-r-300m-ru-test | 042ee97adccd20b0b161130bb3edcba574e9abbb | 2022-03-23T18:27:44.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ru",
"dataset:common_voice",
"transformers",
"hf-asr-leaderboard",
"robust-speech-event",
"model-index"
] | automatic-speech-recognition | false | mobedkova | null | mobedkova/wav2vec2-large-xls-r-300m-ru-test | 12 | null | transformers | 10,623 | ---
language:
- ru
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: Russian Wav2Vec2 XLS-R 300m
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice-7.0
... |
mrm8488/AfricanBERTa | d8817ee58e1a854a2b33604b229fb18356e49b2c | 2021-05-20T18:00:12.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | mrm8488 | null | mrm8488/AfricanBERTa | 12 | null | transformers | 10,624 | Entry not found |
mrm8488/RuPERTa-base-finetuned-ner | c33c7f9b31937060377e5fd630e50dce23cd1b3c | 2021-05-20T18:06:10.000Z | [
"pytorch",
"jax",
"roberta",
"token-classification",
"es",
"transformers",
"autotrain_compatible"
] | token-classification | false | mrm8488 | null | mrm8488/RuPERTa-base-finetuned-ner | 12 | 1 | transformers | 10,625 | ---
language: es
thumbnail:
---
# RuPERTa-base (Spanish RoBERTa) + NER 🎃🏷
This model is a fine-tuned on [NER-C](https://www.kaggle.com/nltkdata/conll-corpora) version of [RuPERTa-base](https://huggingface.co/mrm8488/RuPERTa-base) for **NER** downstream task.
## Details of the downstream task (NER) - Dataset
- [D... |
mrm8488/distilgpt2-finedtuned-meditations | 61c307b75f644636aa761587461f3eda8ba643be | 2021-05-23T10:20:32.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | mrm8488 | null | mrm8488/distilgpt2-finedtuned-meditations | 12 | 1 | transformers | 10,626 | Entry not found |
mrm8488/funnel-transformer-intermediate-mnli | 0d61e100a125b14a793f332085594790fdff1b51 | 2020-11-09T00:09:39.000Z | [
"pytorch",
"funnel",
"text-classification",
"transformers"
] | text-classification | false | mrm8488 | null | mrm8488/funnel-transformer-intermediate-mnli | 12 | null | transformers | 10,627 | Entry not found |
mrm8488/t5-base-finetuned-tab_fact | f3ccb2da496d7757953e8f68cdb20f5cfab672ae | 2021-06-23T13:04:31.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-tab_fact | 12 | null | transformers | 10,628 | Entry not found |
napsternxg/scibert_scivocab_cased_SDU21_AI | 9a1bcabf4e9905d0633a5c3c72aba58188b5c364 | 2021-05-20T01:08:08.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | napsternxg | null | napsternxg/scibert_scivocab_cased_SDU21_AI | 12 | null | transformers | 10,629 | scibert_scivocab_cased submission for SDU21 Task 1 AI
|
napsternxg/scibert_scivocab_uncased_ft_SDU21_AI | 2cc94528633a521bf71a3d64794941fdd9ce54a3 | 2021-05-20T01:09:59.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | napsternxg | null | napsternxg/scibert_scivocab_uncased_ft_SDU21_AI | 12 | null | transformers | 10,630 | scibert_scivocab_uncased_ft MLM pretrained on SDU21 Task 1 + 2
|
ncoop57/code-clippy-125M-py | 8b49d56310bcbbfb6c6d02c28e2becba641d5a20 | 2021-12-29T13:11:41.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | ncoop57 | null | ncoop57/code-clippy-125M-py | 12 | null | transformers | 10,631 | Entry not found |
neuralspace-reverie/indic-transformers-bn-bert | 571ae80ab32841d55a114ab44708c4e9eb3fe3fc | 2021-05-20T01:33:26.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"bn",
"transformers",
"MaskedLM",
"Bengali",
"autotrain_compatible"
] | fill-mask | false | neuralspace-reverie | null | neuralspace-reverie/indic-transformers-bn-bert | 12 | null | transformers | 10,632 | ---
language:
- bn
tags:
- MaskedLM
- Bengali
---
# Indic-Transformers Bengali BERT
## Model description
This is a BERT language model pre-trained on ~3 GB of monolingual training corpus. The pre-training data was majorly taken from [OSCAR](https://oscar-corpus.com/).
This model can be fine-tuned on various downstrea... |
neuralspace-reverie/indic-transformers-bn-xlmroberta | 2a97580fb72a18525d8d071dcc9a3bb348f196cf | 2020-12-11T21:57:15.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"fill-mask",
"bn",
"transformers",
"MaskedLM",
"Bengali",
"XLMRoBERTa",
"Question-Answering",
"Token Classification",
"Text Classification",
"autotrain_compatible"
] | fill-mask | false | neuralspace-reverie | null | neuralspace-reverie/indic-transformers-bn-xlmroberta | 12 | null | transformers | 10,633 | ---
language:
- bn
tags:
- MaskedLM
- Bengali
- XLMRoBERTa
- Question-Answering
- Token Classification
- Text Classification
---
# Indic-Transformers Bengali XLMRoBERTa
## Model description
This is a XLMRoBERTa language model pre-trained on ~3 GB of monolingual training corpus. The pre-training data was majorly taken... |
openclimatefix/metnet-2 | bf3ff79ede5c30bf69aad7e51b4be03eb9bb7798 | 2022-02-02T13:26:42.000Z | [
"pytorch",
"transformers"
] | null | false | openclimatefix | null | openclimatefix/metnet-2 | 12 | null | transformers | 10,634 | Entry not found |
openclimatefix/metnet | bd97bbd638cad466f9d58739c1a7381270a6fd28 | 2022-02-02T13:26:32.000Z | [
"pytorch",
"transformers"
] | null | false | openclimatefix | null | openclimatefix/metnet | 12 | 1 | transformers | 10,635 | Entry not found |
pablouribe/xls-r-spanish-test | a3da82ef93f7e26dc4fcd27585a24de330f39f9c | 2022-03-23T18:27:46.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_7_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_7_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | pablouribe | null | pablouribe/xls-r-spanish-test | 12 | null | transformers | 10,636 | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: xls-r-spanish-test
results:
- task:
name: Speech Recognitio... |
para-zhou/cunlp-gpt2-dialog | 8e7cce7792a2198a08de9c06a6aa661cf6a68f6e | 2021-05-23T10:56:01.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | para-zhou | null | para-zhou/cunlp-gpt2-dialog | 12 | null | transformers | 10,637 | Entry not found |
patrickvonplaten/wav2vec2-100m-mls-german-ft-2 | e73289c8ed3b69de81554d4497ece7a715a760e9 | 2021-11-16T00:01:09.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:multilingual_librispeech",
"transformers",
"multilingual_librispeech",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-100m-mls-german-ft-2 | 12 | null | transformers | 10,638 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- multilingual_librispeech
- generated_from_trainer
datasets:
- multilingual_librispeech
model-index:
- name: wav2vec2-100m-mls-german-ft-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had a... |
patrickvonplaten/wav2vec2-base-100h-2nd-try | 7f9ffca91cd9d03f84843abe410844e375448646 | 2021-11-04T15:41:08.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"transformers",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-base-100h-2nd-try | 12 | null | transformers | 10,639 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
license: apache-2.0
widget:
- example_title: IEMOCAP sample 1
src: https://cdn-media.huggingface.co/speech_samples/IEMOCAP_Ses01F_impro03_F013.wav
- example_title: IEMOCAP sample 2
src: https://cdn-media.huggingface.co/speech_... |
patrickvonplaten/wavlm-libri-clean-100h-large | e70e3a062ec399c46008ee55d1fb52c7ba338d5c | 2021-12-17T13:40:58.000Z | [
"pytorch",
"tensorboard",
"wavlm",
"automatic-speech-recognition",
"transformers",
"librispeech_asr",
"generated_from_trainer",
"wavlm_libri_finetune",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wavlm-libri-clean-100h-large | 12 | 1 | transformers | 10,640 | ---
tags:
- automatic-speech-recognition
- librispeech_asr
- generated_from_trainer
- wavlm_libri_finetune
model-index:
- name: wavlm-librispeech-clean-100h-dist
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread... |
persiannlp/mbert-base-parsinlu-entailment | de5fd7fbf87a6f9e157ec1247fa234133f496824 | 2021-09-23T16:19:47.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"fa",
"multilingual",
"dataset:parsinlu",
"transformers",
"entailment",
"parsbert",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0"
] | text-classification | false | persiannlp | null | persiannlp/mbert-base-parsinlu-entailment | 12 | null | transformers | 10,641 | ---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- entailment
- parsbert
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
metrics:
- accuracy
---
# Textual Entailment (مدل برای پاسخ به استلزام منطقی)
This is a model for textual entailment ... |
philschmid/RoBERTa-Banking77 | e45f9df5bcd9e61ee4ffe582d9c0aa3ec1644d60 | 2021-11-04T09:12:24.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:banking77",
"transformers",
"autonlp",
"model-index"
] | text-classification | false | philschmid | null | philschmid/RoBERTa-Banking77 | 12 | null | transformers | 10,642 | ---
tags: autonlp
language: en
widget:
- text: "I am still waiting on my card?"
datasets:
- banking77
model-index:
- name: RoBERTa-Banking77
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: "BANKING77"
type: banking77
metrics:
- name: Accur... |
pkushiqiang/bert-degree-major-ner-1000 | f0b5306bd4c4304a9142fff08314ac6255066380 | 2022-02-28T08:05:25.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | pkushiqiang | null | pkushiqiang/bert-degree-major-ner-1000 | 12 | null | transformers | 10,643 | Entry not found |
proycon/bert-ner-cased-sonar1-nld | d3343525caf1d15d2adc7a8e9fb56345fc145019 | 2021-05-20T03:06:13.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | proycon | null | proycon/bert-ner-cased-sonar1-nld | 12 | null | transformers | 10,644 | Entry not found |
remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization | 5a985e99440eed91e9227f5393257ab43a4712d8 | 2021-05-20T04:14:02.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | remi | null | remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization | 12 | null | transformers | 10,645 | Entry not found |
scaperex/online-harassment-bert2 | dcb1fbef60973be645c4b0e8ba8a560561b2d491 | 2021-07-14T15:48:43.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | scaperex | null | scaperex/online-harassment-bert2 | 12 | null | transformers | 10,646 | Entry not found |
seiya/oubiobert-base-uncased | 694c027b394acd2390e7cbcc4e3242e7c893ab72 | 2021-05-20T05:10:40.000Z | [
"pytorch",
"jax",
"bert",
"pretraining",
"arxiv:2005.07202",
"transformers",
"exbert",
"license:apache-2.0"
] | null | false | seiya | null | seiya/oubiobert-base-uncased | 12 | 1 | transformers | 10,647 | ---
tags:
- exbert
license: apache-2.0
---
# ouBioBERT-Base, Uncased
Bidirectional Encoder Representations from Transformers for Biomedical Text Mining by Osaka University (ouBioBERT) is a language model based on the BERT-Base (Devlin, et al., 2019) architecture. We pre-trained ouBioBERT on PubMed abstracts from the ... |
sello-ralethe/roberta-base-generics-mlm | 709e5ec7f584c9129240352667c85e723d8815f5 | 2021-05-20T20:10:26.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | sello-ralethe | null | sello-ralethe/roberta-base-generics-mlm | 12 | null | transformers | 10,648 | Entry not found |
sentence-transformers/nli-distilbert-base-max-pooling | 9ce8088f2aa3325e07ef0f13ac79e2887213857a | 2022-06-16T00:49:26.000Z | [
"pytorch",
"tf",
"distilbert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/nli-distilbert-base-max-pooling | 12 | null | sentence-transformers | 10,649 | ---
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... |
shubh2014shiv/jp_review_sentiments_amzn | 63c259ce5070cf73ecff79c1d3808096bf56dd45 | 2021-11-06T14:18:29.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | shubh2014shiv | null | shubh2014shiv/jp_review_sentiments_amzn | 12 | null | transformers | 10,650 | # Steps to use this model
This model uses tokenizer 'rinna/japanese-roberta-base'. Therefore, below steps are critical to run the model correctly.
1. Create a local root directory on your system and new python environment.
2. Install below requirements
```
transformers==4.12.2
torch==1.10.0
numpy==1.21.3
pandas==1.3... |
slider/simcse-chinese-roberta-wwm-ext | 987d39fd06fafa8bfc3b2dc809c142e81a038f74 | 2021-12-10T03:26:18.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | slider | null | slider/simcse-chinese-roberta-wwm-ext | 12 | 1 | transformers | 10,651 | Entry not found |
socialmediaie/TRAC2020_IBEN_B_bert-base-multilingual-uncased | c99643eba2430b5ed81cc05f49f059995552fa8f | 2021-05-20T07:04:58.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | socialmediaie | null | socialmediaie/TRAC2020_IBEN_B_bert-base-multilingual-uncased | 12 | null | transformers | 10,652 | # Multilingual Joint Fine-tuning of Transformer models for identifying Trolling, Aggression and Cyberbullying at TRAC 2020
Models and predictions for submission to TRAC - 2020 Second Workshop on Trolling, Aggression and Cyberbullying.
Our trained models as well as evaluation metrics during traing are available at: ht... |
soikit/chinese-bert-wwm-chinese_bert_wwm2 | 7c70bff0892479e336ad12714d0144f0a523d049 | 2021-10-20T16:49:24.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-generation",
"transformers"
] | text-generation | false | soikit | null | soikit/chinese-bert-wwm-chinese_bert_wwm2 | 12 | null | transformers | 10,653 | Entry not found |
sosuke/ease-roberta-base | 28eb51f87096ed7e9c38b274c10ab77d656cf2c9 | 2021-12-29T08:04:13.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | sosuke | null | sosuke/ease-roberta-base | 12 | null | transformers | 10,654 | Entry not found |
spencerh/centerpartisan | 2c37b7a79b45517d0ac3c24cb324bcf3ca910c1d | 2021-04-23T20:44:08.000Z | [
"pytorch",
"tf",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | spencerh | null | spencerh/centerpartisan | 12 | null | transformers | 10,655 | Entry not found |
sshleifer/student_pegasus_xsum_16_4 | 031d3bf009727b7e0e488b7353253f9035736df1 | 2020-08-27T21:24:12.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sshleifer | null | sshleifer/student_pegasus_xsum_16_4 | 12 | null | transformers | 10,656 | Entry not found |
sshleifer/t5-base-cnn | d23d8b32609b5ddcabc3a8288b7440dee0de479a | 2021-06-23T14:25:31.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sshleifer | null | sshleifer/t5-base-cnn | 12 | null | transformers | 10,657 | Entry not found |
suwani/BERT_NER_Ep5-finetuned-ner | 1406ac38bcf29398efebe9368feb4aaff6f41ba8 | 2021-10-11T03:06:42.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | suwani | null | suwani/BERT_NER_Ep5-finetuned-ner | 12 | null | transformers | 10,658 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_NER_Ep5-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... |
suwani/BERT_NER_Ep5_PAD_50-finetuned-ner | 06a9cc9b04c3c34a8f5930363a9623e85abc29f5 | 2021-10-27T13:13:15.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | suwani | null | suwani/BERT_NER_Ep5_PAD_50-finetuned-ner | 12 | null | transformers | 10,659 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_NER_Ep5_PAD_50-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... |
suwani/BERT_NER_Ep6_PAD_50-finetuned-ner | 262d5e853661ab7da350c61b50e06c0442d23da7 | 2021-10-27T10:28:40.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | suwani | null | suwani/BERT_NER_Ep6_PAD_50-finetuned-ner | 12 | null | transformers | 10,660 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_NER_Ep6_PAD_50-finetuned-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... |
team-writing-assistant/t5-base-c4jfleg | 2a7832d6236f8f9fc7889f6276c90c5fa7131559 | 2021-11-19T11:57:03.000Z | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | team-writing-assistant | null | team-writing-assistant/t5-base-c4jfleg | 12 | 2 | transformers | 10,661 | # Model Description:
To create t5-base-c4jfleg model, T5-base model is fine-tuned on the [**JFLEG dataset**](https://huggingface.co/datasets/jfleg) and [**C4 200M dataset**](https://huggingface.co/datasets/liweili/c4_200m) by taking around 3000 examples from each with the objective of grammar correction.
The original... |
tesemnikov-av/rubert-ner-toxicity | c21271fd92a1f99b50c8d62a9b28585546169993 | 2022-02-08T12:52:32.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tesemnikov-av | null | tesemnikov-av/rubert-ner-toxicity | 12 | null | transformers | 10,662 | ---
widget:
- text: "Ну ты и придурок!!"
---
NER Toxic models
Fine-tuning [cointegrated/rubert-tiny-toxicity](https://huggingface.co/cointegrated/rubert-tiny-toxicity) model on data from [toxic_dataset_ner](https://huggingface.co/datasets/tesemnikov-av/toxic_dataset_ner)
language: RU
```python
!pip inst... |
thomwolf/codeparrot-small | f350f6111154ca2acbcf2851846da96fbc755a2d | 2021-07-27T22:19:21.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | thomwolf | null | thomwolf/codeparrot-small | 12 | null | transformers | 10,663 | Entry not found |
tugstugi/bert-large-mongolian-uncased | 6583581fdb3cd1daf61c76a0efdc8eb543340427 | 2021-05-20T08:19:28.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"mn",
"arxiv:1810.04805",
"transformers",
"mongolian",
"uncased",
"autotrain_compatible"
] | fill-mask | false | tugstugi | null | tugstugi/bert-large-mongolian-uncased | 12 | 3 | transformers | 10,664 | ---
language: "mn"
tags:
- bert
- mongolian
- uncased
---
# BERT-LARGE-MONGOLIAN-UNCASED
[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://... |
xkang/distilbert-base-uncased-finetuned-imdb-whole-word-masking | 872600ba41cc8981670fabb6618bff8790cd1dfc | 2021-12-27T07:35:23.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"fill-mask",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | xkang | null | xkang/distilbert-base-uncased-finetuned-imdb-whole-word-masking | 12 | null | transformers | 10,665 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: distilbert-base-uncased-finetuned-imdb-whole-word-masking
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comple... |
yhavinga/mt5-base-mixednews-nl | f05412c44b892bdc837d107904475afac49c71c4 | 2021-03-13T08:19:42.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"dutch",
"dataset:xsum_nl",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | yhavinga | null | yhavinga/mt5-base-mixednews-nl | 12 | null | transformers | 10,666 | ---
tags:
- summarization
language:
- dutch
datasets:
- xsum_nl
widget:
- text: "Onderzoekers ontdekten dat vier van de vijf kinderen in Engeland die op school lunches hadden gegeten, op school voedsel hadden geprobeerd dat ze thuis niet hadden geprobeerd.De helft van de ondervraagde ouders zei dat hun kinderen hadden... |
yigitbekir/turkish-bert-uncased-sentiment | 39c2ac210059db0249fa3fd7893bffad9f577a76 | 2021-05-20T09:29:34.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | yigitbekir | null | yigitbekir/turkish-bert-uncased-sentiment | 12 | null | transformers | 10,667 | Entry not found |
yongzx/gpt2-finetuned-oscar-de | e66c8ee26fcc7bdea851c3135f8163a2e1b8639e | 2021-12-09T16:44:10.000Z | [
"pytorch",
"gpt2",
"feature-extraction",
"de",
"dataset:oscar",
"transformers",
"text-generation",
"license:mit"
] | feature-extraction | false | yongzx | null | yongzx/gpt2-finetuned-oscar-de | 12 | null | transformers | 10,668 | ---
language:
- de
tags:
- text-generation
license: mit
datasets:
- oscar
widget:
- text: "Mein Name ist Anna. Ich komme aus Österreich und "
---
# GPT-2 finetuned on German Dataset
### Tokenizer
We first trained a tokenizer on OSCAR's `unshuffled_original_de` German data subset by following the training of GPT2 tok... |
yoshitomo-matsubara/bert-large-uncased-mnli | 2c9bb0f160f5d4cf405348abcb9d46342132e926 | 2021-05-29T21:32:31.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:mnli",
"dataset:ax",
"transformers",
"mnli",
"ax",
"glue",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-large-uncased-mnli | 12 | null | transformers | 10,669 | ---
language: en
tags:
- bert
- mnli
- ax
- glue
- torchdistill
license: apache-2.0
datasets:
- mnli
- ax
metrics:
- accuracy
---
`bert-large-uncased` fine-tuned on MNLI dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.research.google.com/github/... |
wietsedv/xlm-roberta-base-ft-udpos28-ar | fc4e7b640067f7e5db7e0be233d650dd3628719e | 2022-02-25T09:58:02.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"ar",
"dataset:universal_dependencies",
"transformers",
"part-of-speech",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | wietsedv | null | wietsedv/xlm-roberta-base-ft-udpos28-ar | 12 | null | transformers | 10,670 |
---
language:
- ar
license: apache-2.0
library_name: transformers
tags:
- part-of-speech
- token-classification
datasets:
- universal_dependencies
metrics:
- accuracy
model-index:
- name: xlm-roberta-base-ft-udpos28-ar
results:
- task:
type: token-classification
name: Part-of-Speech Tagging
datas... |
saptarshidatta96/finetuning-sentiment-model-3000-samples | 5cf9bbeaa64d950d8b9a7ca397bdd66d93525658 | 2022-02-25T15:20:10.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | saptarshidatta96 | null | saptarshidatta96/finetuning-sentiment-model-3000-samples | 12 | null | transformers | 10,671 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... |
inovex/multi2convai-logistics-en-bert | 85f98ab937bfd02e29a7e28e5d57bb4765152862 | 2022-03-01T08:53:59.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-logistics-en-bert | 12 | null | transformers | 10,672 | ---
tags:
- text-classification
widget:
- text: "Where can I put the parcel?"
license: mit
language: en
---
# Multi2ConvAI-Logistics: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Logistics (more details about our use cases: ([en](http... |
inovex/multi2convai-quality-de-bert | 969f8fb42109e842afe13bdb50d09c72b8e0bbb5 | 2022-03-01T09:00:15.000Z | [
"pytorch",
"bert",
"text-classification",
"de",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-quality-de-bert | 12 | null | transformers | 10,673 | ---
tags:
- text-classification
widget:
- text: "Starte das Programm"
license: mit
language: de
---
# Multi2ConvAI-Quality: finetuned Bert for German
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-it-mbert | b220b01a2efa5cfed2436ca57e4c4bf54d54b4cd | 2022-03-01T09:02:26.000Z | [
"pytorch",
"bert",
"text-classification",
"it",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-quality-it-mbert | 12 | null | transformers | 10,674 | ---
tags:
- text-classification
widget:
- text: "Avviare il programma"
license: mit
language: it
---
# Multi2ConvAI-Quality: finetuned MBert for Italian
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Quality (more details about our use cases: ([en](https://multi2... |
ghadeermobasher/BC4_Original-BiomedNLP-PubMedBERT-base-uncased-abstract | e32328fa391e1eb3b937f91c230dab8683d97f8b | 2022-03-03T14:45:58.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4_Original-BiomedNLP-PubMedBERT-base-uncased-abstract | 12 | null | transformers | 10,675 | Entry not found |
ghadeermobasher/BC4_Modified_BiomedNLP-PubMedBERT-base-uncased-abstract | 3e502f9f2579f4c4108aae7ed4e5253d95d9b232 | 2022-02-25T21:18:15.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4_Modified_BiomedNLP-PubMedBERT-base-uncased-abstract | 12 | null | transformers | 10,676 | Entry not found |
anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-4 | 7b4c0ed9bd398f81a00569d8ada5f4e109f5fdd6 | 2022-02-25T21:12:44.000Z | [
"pytorch",
"bert",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | anas-awadalla | null | anas-awadalla/spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-4 | 12 | null | transformers | 10,677 | ---
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: spanbert-base-cased-few-shot-k-32-finetuned-squad-seed-4
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove t... |
nsi319/xlnet-base-cased-finetuned-app | 11a6dae1231e2505c687c4e91c40781036bf0cdd | 2022-02-27T10:52:49.000Z | [
"pytorch",
"xlnet",
"text-classification",
"en",
"transformers",
"mobile app descriptions",
"playstore",
"license:mit"
] | text-classification | false | nsi319 | null | nsi319/xlnet-base-cased-finetuned-app | 12 | null | transformers | 10,678 | ---
language: "en"
thumbnail: "https://huggingface.co/nsi319"
tags:
- xlnet
- pytorch
- text-classification
- mobile app descriptions
- playstore
license: "mit"
inference: true
---
# Mobile App Classification
## Model description
XLNet is a new unsupervised language representation learning method based on a novel ge... |
asini/wav2vec2-timit-demo | a076c094708a22f392e286d8aee7ff7dcda35f0a | 2022-03-01T10:37:06.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | asini | null | asini/wav2vec2-timit-demo | 12 | null | transformers | 10,679 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-timit-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-timit-... |
Andrey1989/mbert-finetuned-ner | a60a40c0f4842458f777c5a1a13f53c4d36174b2 | 2022-06-13T19:46:59.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | Andrey1989 | null | Andrey1989/mbert-finetuned-ner | 12 | null | transformers | 10,680 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mbert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
args: lv
... |
batterydata/batterybert-uncased-squad-v1 | 5cf7334ad5096f21556380873c5a806cf445b806 | 2022-03-05T13:52:33.000Z | [
"pytorch",
"bert",
"question-answering",
"en",
"dataset:squad",
"dataset:batterydata/battery-device-data-qa",
"transformers",
"question answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | batterydata | null | batterydata/batterybert-uncased-squad-v1 | 12 | null | transformers | 10,681 | ---
language: en
tags: question answering
license: apache-2.0
datasets:
- squad
- batterydata/battery-device-data-qa
metrics: squad
---
# BatteryBERT-uncased for QA
**Language model:** batterybert-uncased
**Language:** English
**Downstream-task:** Extractive QA
**Training data:** SQuAD v1
**Eval d... |
batterydata/bert-base-uncased-abstract | 383638f165004b6c8c2f3fdb3d1d2ce794b8b0b5 | 2022-03-05T14:44:13.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:batterydata/paper-abstracts",
"transformers",
"Text Classification",
"license:apache-2.0"
] | text-classification | false | batterydata | null | batterydata/bert-base-uncased-abstract | 12 | null | transformers | 10,682 | ---
language: en
tags: Text Classification
license: apache-2.0
datasets:
- batterydata/paper-abstracts
metrics: glue
---
# BERT-base-uncased for Battery Abstract Classification
**Language model:** bert-base-uncased
**Language:** English
**Downstream-task:** Text Classification
**Training data:** train... |
cnu/distilbert-base-uncased-finetuned-cola | 3390b50b51f566b9bb7e9e6059688b9e92b83e40 | 2022-03-02T07:30:35.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | cnu | null | cnu/distilbert-base-uncased-finetuned-cola | 12 | null | transformers | 10,683 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... |
clisi2000/distilbert-base-uncased-finetuned-emotion | 3caab60c0f4e263855d0dafa37419e9a7d5b94c9 | 2022-03-06T07:09:00.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | clisi2000 | null | clisi2000/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,684 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
ttmusic/distilbert-base-uncased-finetuned-imdb | 9f2aa94ccde5cc450648bc578e9157fe6b92b752 | 2022-03-06T01:28:38.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | ttmusic | null | ttmusic/distilbert-base-uncased-finetuned-imdb | 12 | null | transformers | 10,685 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: distilbert-base-uncased-finetuned-imdb
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove ... |
bishnu/finetuning-sentiment-model-3000-samples | 0ad49b15cca93b9ca27ca681cc2eec49576e8764 | 2022-03-09T17:05:15.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | bishnu | null | bishnu/finetuning-sentiment-model-3000-samples | 12 | null | transformers | 10,686 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
met... |
spy24/autonlp-optimized-paraphrasing-615217541 | 7d402f22bfd7b781ca1fb020554a95182ad47f79 | 2022-03-07T08:56:14.000Z | [
"pytorch",
"t5",
"text2text-generation",
"unk",
"dataset:spy24/autonlp-data-optimized-paraphrasing",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | spy24 | null | spy24/autonlp-optimized-paraphrasing-615217541 | 12 | null | transformers | 10,687 | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- spy24/autonlp-data-optimized-paraphrasing
co2_eq_emissions: 1.166696812121839
---
# Model Trained Using AutoNLP
- Problem type: Summarization
- Model ID: 615217541
- CO2 Emissions (in grams): 1.166696812121839
## Validation Metrics
- Lo... |
abhishek/autonlp-swahili-sentiment-615517563 | e66110eb541d862b2d257254b5dea87757f168fb | 2022-03-07T12:54:03.000Z | [
"pytorch",
"bert",
"text-classification",
"unk",
"dataset:abhishek/autonlp-data-swahili-sentiment",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | abhishek | null | abhishek/autonlp-swahili-sentiment-615517563 | 12 | null | transformers | 10,688 | ---
tags: autonlp
language: unk
widget:
- text: "I love AutoNLP 🤗"
datasets:
- abhishek/autonlp-data-swahili-sentiment
co2_eq_emissions: 1.9057858628956459
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 615517563
- CO2 Emissions (in grams): 1.9057858628956459
## Validation ... |
zdepablo/distilbert-base-uncased-finetuned-emotion | 14b8eecb0c52f0a6435a32f675f9154354ed78d9 | 2022-03-09T23:04:59.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | zdepablo | null | zdepablo/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,689 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
Kaveh8/autonlp-imdb_rating-625417974 | 5670bb192c112974e4047d211228c29c1906db16 | 2022-03-10T13:20:41.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:Kaveh8/autonlp-data-imdb_rating",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | Kaveh8 | null | Kaveh8/autonlp-imdb_rating-625417974 | 12 | null | transformers | 10,690 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- Kaveh8/autonlp-data-imdb_rating
co2_eq_emissions: 0.7952957276830314
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 625417974
- CO2 Emissions (in grams): 0.7952957276830314
## Validation Metrics
... |
haddadalwi/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-islamic-squad | 1f444815eb2e009edf195c6d98fecdce594459c8 | 2022-03-28T05:04:56.000Z | [
"pytorch",
"tensorboard",
"bert",
"question-answering",
"dataset:squad_v2",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | haddadalwi | null | haddadalwi/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-islamic-squad | 12 | null | transformers | 10,691 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-islamic-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should proba... |
cloudblack/bert-base-finetuned-sts | 712f7c3f93b6b4c4c7453639d4ab8b927586d4e3 | 2022-03-13T11:13:45.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | cloudblack | null | cloudblack/bert-base-finetuned-sts | 12 | null | transformers | 10,692 | Entry not found |
anwesham/mbert_hi_ur | e8e2905183d1e248e172b1dba6b6c489c8e9f59d | 2022-03-13T02:36:43.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | anwesham | null | anwesham/mbert_hi_ur | 12 | null | transformers | 10,693 | Entry not found |
clapika2010/flights_finetuned | 5ca4dc9495a0882fb748b2cf2584e6b0ff4ad2ae | 2022-03-12T07:46:54.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | clapika2010 | null | clapika2010/flights_finetuned | 12 | null | transformers | 10,694 | Entry not found |
RobertoMCA97/distilbert-base-uncased-finetuned-emotion | b8bf3e877355e17b6a9b03d5b1f8ca5e01457c6b | 2022-03-12T17:11:44.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | RobertoMCA97 | null | RobertoMCA97/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,695 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
Ramu/distilbert-base-uncased-finetuned-emotion | 4ea7758319c1416db8e70c5d32cf3a277d368441 | 2022-03-13T14:27:54.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Ramu | null | Ramu/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,696 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
aGabillon/distilbert-base-uncased-finetuned-emotion | c9909c051291b19611466538f34468c84865c715 | 2022-03-13T04:19:27.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | aGabillon | null | aGabillon/distilbert-base-uncased-finetuned-emotion | 12 | null | transformers | 10,697 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
alexhf90/Clasificacion_sentimientos | 15549210e7ab5a218e13a67ff6047c4b262b0148 | 2022-03-15T22:20:11.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | alexhf90 | null | alexhf90/Clasificacion_sentimientos | 12 | 1 | transformers | 10,698 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Clasificacion_sentimientos
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comm... |
anton-l/xtreme_s_xlsr_300m_mls | e549e826c377de13e756208ce95e6971465078a7 | 2022-04-03T18:54:35.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"dataset:google/xtreme_s",
"transformers",
"google/xtreme_s",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anton-l | null | anton-l/xtreme_s_xlsr_300m_mls | 12 | 1 | transformers | 10,699 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- google/xtreme_s
- generated_from_trainer
datasets:
- google/xtreme_s
model-index:
- name: xtreme_s_xlsr_mls
results: []
---
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