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/wav2vec2-large-xls-r-1b-Swedish | e88c671af0d195339661c0c3afe8e806e0af353f | 2022-03-24T11:58:17.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"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-large-xls-r-1b-Swedish | 11 | null | transformers | 11,100 | ---
language:
- sv-SE
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-large-xls-r-1b-Swedish
results:
- task:
type: automatic-speech-recognition
name: Sp... |
ktrapeznikov/scibert_scivocab_uncased_squad_v2 | 2a507379876427c3b1ddbea6ef7825c36c5a7ddb | 2021-05-19T21:11:07.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | ktrapeznikov | null | ktrapeznikov/scibert_scivocab_uncased_squad_v2 | 11 | null | transformers | 11,101 | ### Model
**[`allenai/scibert_scivocab_uncased`](https://huggingface.co/allenai/scibert_scivocab_uncased)** fine-tuned on **[`SQuAD V2`](https://rajpurkar.github.io/SQuAD-explorer/)** using **[`run_squad.py`](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_squad.py)**
### Traini... |
kurianbenoy/bert-finetuned-ner | c0c6c18649ac5e30ad860ef747854c8645939d04 | 2022-02-23T11:48:55.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | kurianbenoy | null | kurianbenoy/bert-finetuned-ner | 11 | null | transformers | 11,102 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: c... |
l3cube-pune/hate-roberta-hasoc-hindi | ee9573aeb024582b097a46522825dc0b9a7e544f | 2021-10-30T18:05:58.000Z | [
"pytorch",
"tf",
"roberta",
"text-classification",
"hi",
"dataset:HASOC 2021",
"arxiv:2110.12200",
"transformers",
"license:cc-by-4.0"
] | text-classification | false | l3cube-pune | null | l3cube-pune/hate-roberta-hasoc-hindi | 11 | null | transformers | 11,103 | ---
language: hi
tags:
- roberta
license: cc-by-4.0
datasets:
- HASOC 2021
widget:
- text: "I like you. </s></s> I love you."
---
## hate-roberta-hasoc-hindi
hate-roberta-hasoc-hindi is a binary hate speech model fine-tuned on Hindi Hasoc Hate Speech Dataset 2021.
The label mappings are 0 -> None, 1 -> Hate.
More d... |
lewtun/xlm-roberta-base-finetuned-marc-de | fa4a1282887d16b28a4dad4b4a6b7645b2b5b3cc | 2021-10-16T11:38:18.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"text-classification",
"dataset:amazon_reviews_multi",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | lewtun | null | lewtun/xlm-roberta-base-finetuned-marc-de | 11 | null | transformers | 11,104 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
model-index:
- name: xlm-roberta-base-finetuned-marc-de
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 re... |
log0/wav2vec2-base-lang-id | 9828f4fd957e470cc9d536d4cdda2917ead0eaf8 | 2022-02-18T14:36:19.000Z | [
"pytorch",
"tensorboard",
"hubert",
"audio-classification",
"transformers"
] | audio-classification | false | log0 | null | log0/wav2vec2-base-lang-id | 11 | null | transformers | 11,105 | Entry not found |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_grad | d10a675e306e33514b54b10ce90d7ca4ad1940ca | 2021-10-29T01:09:24.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_grad | 11 | null | transformers | 11,106 | Entry not found |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_5e6_bb_lr_5e6_wu_25k_ep_10_grad_adam | c75e98654ff02a47f5388c3edfb4616fe5bc63ec | 2021-10-31T07:44:13.000Z | [
"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_25k_ep_10_grad_adam | 11 | null | transformers | 11,107 | Entry not found |
m3hrdadfi/albert-fa-base-v2-clf-digimag | 96f4b588dee49f8e41df85e83d3042872a5db952 | 2020-12-26T08:28:59.000Z | [
"pytorch",
"tf",
"albert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | m3hrdadfi | null | m3hrdadfi/albert-fa-base-v2-clf-digimag | 11 | null | transformers | 11,108 | ---
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... |
m3hrdadfi/albert-zwnj-wnli-mean-tokens | 3b8686736842a2228fcdc2329c5dea18114c5784 | 2021-06-28T17:42:32.000Z | [
"pytorch",
"albert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | feature-extraction | false | m3hrdadfi | null | m3hrdadfi/albert-zwnj-wnli-mean-tokens | 11 | null | sentence-transformers | 11,109 | ---
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# Sentence Embeddings with `albert-zwnj-wnli-mean-tokens`
## Usage (Sentence-Transformers)
Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) install... |
m3hrdadfi/bert-fa-base-uncased-farstail | 43915c0a3b8fe90b679368e8f66c56bbbd473d82 | 2021-05-28T06:02:52.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | m3hrdadfi | null | m3hrdadfi/bert-fa-base-uncased-farstail | 11 | null | transformers | 11,110 | ---
language: fa
license: apache-2.0
---
# FarsTail + ParsBERT
Please follow the [FarsTail](https://github.com/dml-qom/FarsTail) repo for the latest information about the dataset. For accessing the beneficiary models from this dataset, check out the [Sentence-Transformer](https://github.com/m3hrdadfi/sentence-transfo... |
macedonizer/blaze-koneski | d871ee88171960c3b99ba84a63a6bb8e93fbffa8 | 2021-09-22T08:58:34.000Z | [
"pytorch",
"gpt2",
"text-generation",
"mk",
"dataset:wiki-mk",
"dataset:blaze-koneski-poetry",
"transformers",
"license:apache-2.0"
] | text-generation | false | macedonizer | null | macedonizer/blaze-koneski | 11 | null | transformers | 11,111 | ---
language:
- mk
thumbnail: https://huggingface.co/macedonizer/blaze-koneski/blaze-koneski.jpg
license: apache-2.0
datasets:
- wiki-mk
- blaze-koneski-poetry
---
# blaze-koneski
GPT-2 type of model. We finetuned macedonizer/mk-gpt-2 with Blaze Koneski's poetry.
## About Blaze Koneski
Born in a village near Prilep i... |
malay-huggingface/t5-super-tiny-bahasa-cased | 0254fae6ae8e24db9806111d5db979e54bc69352 | 2021-09-05T13:17:40.000Z | [
"pytorch",
"t5",
"feature-extraction",
"ms",
"transformers"
] | feature-extraction | false | malay-huggingface | null | malay-huggingface/t5-super-tiny-bahasa-cased | 11 | null | transformers | 11,112 | ---
language: ms
---
# t5-super-tiny-bahasa-cased
Pretrained T5 super-tiny language model for Malay.
## Pretraining Corpus
`t5-super-tiny-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, baha... |
mbeukman/xlm-roberta-base-finetuned-hausa-finetuned-ner-swahili | 478845b9ef072a42229850adfe6ed5838d33030a | 2021-11-25T09:03:58.000Z | [
"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-hausa-finetuned-ner-swahili | 11 | null | transformers | 11,113 | ---
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-hausa-finetuned-ner-swahili
This is a token classification (spe... |
mbeukman/xlm-roberta-base-finetuned-wolof-finetuned-ner-wolof | 3e4fa1bb16d8ed422e603817c06dee81269479c0 | 2021-11-25T09:05:13.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"wo",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-wolof-finetuned-ner-wolof | 11 | null | transformers | 11,114 | ---
language:
- wo
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "SAFIYETU BÉEY Céy Koronaa !"
---
# xlm-roberta-base-finetuned-wolof-finetuned-ner-wolof
This is a token classification (specifically NER) model that fine-tuned [xlm-roberta-base-finetuned-wolof](https://huggin... |
michaelrglass/bert-large-uncased-sspt | 440130f131d0b86f4af1baa423b5d1813f20506a | 2021-05-19T23:26:01.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | michaelrglass | null | michaelrglass/bert-large-uncased-sspt | 11 | null | transformers | 11,115 | Entry not found |
monsoon-nlp/ar-seq2seq-gender-decoder | 03e1e51b88556e6cddba1da871345354f8d20b97 | 2021-05-19T23:53:24.000Z | [
"pytorch",
"bert",
"text-generation",
"ar",
"transformers"
] | text-generation | false | monsoon-nlp | null | monsoon-nlp/ar-seq2seq-gender-decoder | 11 | null | transformers | 11,116 | ---
language: ar
---
# ar-seq2seq-gender (decoder)
This is a seq2seq model (decoder half) to "flip" gender in **first-person** Arabic sentences.
The model can augment your existing Arabic data, or generate counterfactuals
to test a model's decisions (would changing the gender of the subject or speaker change output?)... |
moussaKam/frugalscore_small_deberta_bert-score | 2035337fab8e3bbfd6063a0993cfc0902cc42de7 | 2022-01-28T13:19:20.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:2110.08559",
"transformers"
] | text-classification | false | moussaKam | null | moussaKam/frugalscore_small_deberta_bert-score | 11 | null | transformers | 11,117 | # FrugalScore
FrugalScore is an approach to learn a fixed, low cost version of any expensive NLG metric, while retaining most of its original performance
Paper: https://arxiv.org/abs/2110.08559?context=cs
Project github: https://github.com/moussaKam/FrugalScore
The pretrained checkpoints presented in the paper :
| ... |
mrm8488/ManuERT-for-xqua | ef690580807cb651a7bc5545d52cfb7b9c1b919a | 2021-05-20T00:16:59.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | mrm8488 | null | mrm8488/ManuERT-for-xqua | 11 | null | transformers | 11,118 | Entry not found |
mse30/bart-base-finetuned-xsum | 605fd05ebfb0e6744c9f1844fe33cac1a3948e11 | 2021-10-27T22:13:08.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mse30 | null | mse30/bart-base-finetuned-xsum | 11 | null | transformers | 11,119 | Entry not found |
mujeensung/albert-base-v2_mnli_bc | f7c73a6b7cac7c8123a1a5354e7d90031c5ee8d6 | 2022-02-13T05:23:40.000Z | [
"pytorch",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | mujeensung | null | mujeensung/albert-base-v2_mnli_bc | 11 | null | transformers | 11,120 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: albert-base-v2_mnli_bc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
... |
nimanpra/Fine_Tuned_Spiritual | 82a866e1a9c7cb937fcf6c5962a179e2796ab958 | 2021-06-17T16:09:05.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | nimanpra | null | nimanpra/Fine_Tuned_Spiritual | 11 | null | transformers | 11,121 | Entry not found |
paintingpeter/distilbert-base-uncased-finetuned-clinc | edfb6047f8c7da3d6b60e6b1ab95ded1789112d6 | 2022-01-31T21:55:25.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:clinc_oos",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | paintingpeter | null | paintingpeter/distilbert-base-uncased-finetuned-clinc | 11 | null | transformers | 11,122 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... |
peterchou/unilm-chinese-base | 4a4995e1a5d5fefe6df73749f89bff8a34a48b12 | 2021-05-20T02:33:23.000Z | [
"pytorch",
"jax",
"bert",
"transformers"
] | null | false | peterchou | null | peterchou/unilm-chinese-base | 11 | null | transformers | 11,123 | Entry not found |
phueb/BabyBERTa-2 | 6c88fd5c30fb24189728efc3e9bdebf1d593c9c7 | 2022-01-18T14:44:44.000Z | [
"pytorch",
"roberta",
"fill-mask",
"en",
"dataset:CHILDES",
"transformers",
"BabyBERTa",
"autotrain_compatible"
] | fill-mask | false | phueb | null | phueb/BabyBERTa-2 | 11 | null | transformers | 11,124 | ---
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... |
pierreguillou/bert-large-cased-pt-lenerbr | 02425bad92d1762aeaaf050996991893caf13a89 | 2022-01-04T08:52:43.000Z | [
"pytorch",
"bert",
"fill-mask",
"pt",
"dataset:pierreguillou/lener_br_finetuning_language_model",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | pierreguillou | null | pierreguillou/bert-large-cased-pt-lenerbr | 11 | 2 | transformers | 11,125 | ---
language:
- pt
tags:
- generated_from_trainer
datasets:
- pierreguillou/lener_br_finetuning_language_model
model-index:
- name: checkpoints
results:
- task:
name: Fill Mask
type: fill-mask
dataset:
name: pierreguillou/lener_br_finetuning_language_model
type: pierreguillou/lener_br_f... |
pmthangk09/bert-base-uncased-esnli | f83f679d8fa2d84b82be44b7cf6672ecfb40e7c6 | 2021-05-20T02:46:17.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pmthangk09 | null | pmthangk09/bert-base-uncased-esnli | 11 | null | transformers | 11,126 | Entry not found |
ponteineptique/latin-classical-small | a1d55b6a26d3fb06c9b50c61df2813a39864cb72 | 2020-04-24T16:05:14.000Z | [
"pytorch",
"xlm",
"feature-extraction",
"transformers"
] | feature-extraction | false | ponteineptique | null | ponteineptique/latin-classical-small | 11 | null | transformers | 11,127 | Entry not found |
proycon/bert-ner-cased-conll2002-nld | a2485b58ec02d0c038ce079ab3e7c85010148672 | 2021-05-20T03:05:15.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | proycon | null | proycon/bert-ner-cased-conll2002-nld | 11 | null | transformers | 11,128 | Entry not found |
proycon/bert-pos-cased-deepfrog-nld | 4515aae9f28dc24164f18926086a031376f0586d | 2021-05-20T03:07:09.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | proycon | null | proycon/bert-pos-cased-deepfrog-nld | 11 | null | transformers | 11,129 | Entry not found |
pysentimiento/robertuito-irony | 7e819c8fe295df4d2fdc591ab1b4b9a49e580b15 | 2021-11-22T16:16:45.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:2106.09462",
"arxiv:2111.09453",
"transformers"
] | text-classification | false | pysentimiento | null | pysentimiento/robertuito-irony | 11 | 1 | transformers | 11,130 | # Irony detection in Spanish
## robertuito-irony
Repository: [https://github.com/pysentimiento/pysentimiento/](https://github.com/finiteautomata/pysentimiento/)
Model trained with IRosVA 2019 dataset for irony detection. Base model is [RoBERTuito](https://github.com/pysentimiento/robertuito), a RoBERTa model traine... |
quincyqiang/tesla2 | 90abad32892c3fb43cbb87bef2c64453d253e47e | 2021-05-20T03:52:00.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | quincyqiang | null | quincyqiang/tesla2 | 11 | null | transformers | 11,131 | Entry not found |
raynardj/pmc-med-bio-mlm-roberta-large | c70f6bfb352375382808dfa500a56af7413a4de1 | 2021-11-28T13:57:31.000Z | [
"pytorch",
"roberta",
"fill-mask",
"en",
"transformers",
"autotrain_compatible"
] | fill-mask | false | raynardj | null | raynardj/pmc-med-bio-mlm-roberta-large | 11 | 1 | transformers | 11,132 | ---
language:
- en
tags:
- fill-mask
- roberta
widget:
- text: "Polymerase <mask> Reaction"
---
# PMC pretrained RoBERTa large model
Pretrained on PMC fulltext paragraphs on masked language modeling task, it's mostly biology/ medical papers |
rsvp-ai/bertserini-bert-base-cmrc | 7805b05ac989fed6ed7e30f01ab28b0f90f572b8 | 2021-05-19T00:38:49.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | rsvp-ai | null | rsvp-ai/bertserini-bert-base-cmrc | 11 | null | transformers | 11,133 | Entry not found |
sackoh/bert-base-multilingual-cased-nsmc | 768a6323c657f8184deb554ff976b29dbef2ebde | 2021-05-19T00:50:32.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | sackoh | null | sackoh/bert-base-multilingual-cased-nsmc | 11 | null | transformers | 11,134 | Entry not found |
sagorsarker/codeswitch-nepeng-lid-lince | 37989eb40861b1c6147cabb9a083c33fdb8761c4 | 2021-05-19T01:11:01.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"ne",
"en",
"dataset:lince",
"transformers",
"codeswitching",
"nepali-english",
"language-identification",
"license:mit",
"autotrain_compatible"
] | token-classification | false | sagorsarker | null | sagorsarker/codeswitch-nepeng-lid-lince | 11 | null | transformers | 11,135 | ---
language:
- ne
- en
datasets:
- lince
license: mit
tags:
- codeswitching
- nepali-english
- language-identification
---
# codeswitch-nepeng-lid-lince
This is a pretrained model for **language identification** of `nepali-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home).
This model is tr... |
samitizerxu/wav2vec2-xls-r-300m-fr | bbcb338de18d0bfa3cb111078e182a8df7c54a36 | 2022-03-23T18:33:04.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | samitizerxu | null | samitizerxu/wav2vec2-xls-r-300m-fr | 11 | null | transformers | 11,136 | ---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- fr
- generated_from_trainer
- hf-asr-leaderboard
- robust-speech-event
datasets:
- common_voice
model-index:
- name: wav2vec2-cls-r-300m-fr
results:
- task:
name: Automatic Speech Recognition
type: automatic-spe... |
seduerr/paraphrase | 0ff7d8bd97071e8f5a3d25697984854f343b3598 | 2021-06-23T14:17:58.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | seduerr | null | seduerr/paraphrase | 11 | null | transformers | 11,137 | Entry not found |
seongju/klue-mrc-roberta-base | 967a1cc8fe384411c22a166cc6c659c16add16d6 | 2021-08-09T08:06:23.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | seongju | null | seongju/klue-mrc-roberta-base | 11 | null | transformers | 11,138 | Entry not found |
sergiyvl/ParaPhraserPlus_1epoch | 7b7869921bdeafa33470c0fc4986f17517e54055 | 2021-05-20T05:30:51.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | sergiyvl | null | sergiyvl/ParaPhraserPlus_1epoch | 11 | null | transformers | 11,139 | Entry not found |
sismetanin/mbart_ru_sum_gazeta-ru-sentiment-krnd | f48dcde73805a046fd10292bc488907efda89b31 | 2021-02-21T13:19:50.000Z | [
"pytorch",
"mbart",
"text-classification",
"transformers"
] | text-classification | false | sismetanin | null | sismetanin/mbart_ru_sum_gazeta-ru-sentiment-krnd | 11 | null | transformers | 11,140 | Entry not found |
skylord/wav2vec2-large-xlsr-greek-2 | 00ac229e00fa3743119d3f6152ac3f9247984f62 | 2021-03-31T09:42:31.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"el",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | skylord | null | skylord/wav2vec2-large-xlsr-greek-2 | 11 | null | transformers | 11,141 | ---
language: el
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Greek XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Co... |
sshleifer/student_enro_sum_12_1 | d8ee5fac300d1df4c5adc0ebecd8056909dbe7e0 | 2020-07-18T20:16:27.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sshleifer | null | sshleifer/student_enro_sum_12_1 | 11 | null | transformers | 11,142 | Entry not found |
sshleifer/student_pegasus_cnn_12_2 | d8ce6f11b4a1174c2d0edf3b979a9a1f5232f4c6 | 2020-10-02T03:49:28.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | sshleifer | null | sshleifer/student_pegasus_cnn_12_2 | 11 | null | transformers | 11,143 | Entry not found |
stanford-crfm/durin-gpt2-medium-x343 | fe7e487b4a5109d1190a57b28e4419f3ab972468 | 2022-06-20T10:58:10.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | stanford-crfm | null | stanford-crfm/durin-gpt2-medium-x343 | 11 | null | transformers | 11,144 | Entry not found |
stanford-crfm/expanse-gpt2-small-x777 | 1a3988b4f158d80cf8f72df885ea258783317434 | 2022-06-20T09:32:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | stanford-crfm | null | stanford-crfm/expanse-gpt2-small-x777 | 11 | null | transformers | 11,145 | Entry not found |
stefan-it/wav2vec2-large-xlsr-53-basque | 19cc35f777b8105c807a94b4c0a68ffe3009b18c | 2021-03-29T15:54:40.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"eu",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | stefan-it | null | stefan-it/wav2vec2-large-xlsr-53-basque | 11 | null | transformers | 11,146 | ---
language: eu
datasets:
- common_voice
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Basque Stefan Schweter
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Com... |
sukhendrasingh/finetuning-sentiment-model-3000-samples | eba498245dd43db7e5e6812e0180a6b0bbb08c83 | 2022-02-07T17:20:03.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | sukhendrasingh | null | sukhendrasingh/finetuning-sentiment-model-3000-samples | 11 | null | transformers | 11,147 | ---
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... |
surajp/SanBERTa | 43ee7b437c82b84e0405a3d194a676dd6308dee4 | 2021-05-20T22:03:36.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"sa",
"transformers",
"autotrain_compatible"
] | fill-mask | false | surajp | null | surajp/SanBERTa | 11 | null | transformers | 11,148 | ---
language: sa
---
# RoBERTa trained on Sanskrit (SanBERTa)
**Mode size** (after training): **340MB**
### Dataset:
[Wikipedia articles](https://www.kaggle.com/disisbig/sanskrit-wikipedia-articles) (used in [iNLTK](https://github.com/goru001/nlp-for-sanskrit)).
It contains evaluation set.
[Sanskrit scraps from CL... |
techiaith/wav2vec2-xlsr-ft-cy | 69df7e44646babb4b3edc4abd7ad8885e8d4d5c0 | 2022-06-15T12:37:49.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"cy",
"dataset:common_voice",
"transformers",
"audio",
"hf-asr-leaderboard",
"ken-lm",
"robust-speech-event",
"speech",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | techiaith | null | techiaith/wav2vec2-xlsr-ft-cy | 11 | 3 | transformers | 11,149 | ---
language: cy
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
- ken-lm
- robust-speech-event
- speech
license: apache-2.0
model-index:
- name: wav2vec2-xlsr-ft-cy with KenLM language model (by Bangor University)
results:
- task:
name: Speech Recogni... |
timtarusov/distilbert-base-uncased-finetuned-emotion | 959f361640c433397f05357a6c78d046e7b78e36 | 2022-02-13T08:48:03.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | timtarusov | null | timtarusov/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,150 | ---
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... |
tomascufaro/xls-r-es-test | 4acc7c880e7016dc92e72e46ac93963a25525cd7 | 2022-03-24T11:58:49.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"es",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | tomascufaro | null | tomascufaro/xls-r-es-test | 11 | null | transformers | 11,151 | ---
language:
- es
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- es
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: xls-r-es-test
results:
- task:
name: Automatic Speech ... |
tr3cks/bert-ner-es | 0c770676060b3cfb81b5a5a3a90c236c1ebc3b4b | 2021-05-20T08:04:44.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | tr3cks | null | tr3cks/bert-ner-es | 11 | null | transformers | 11,152 | Entry not found |
uclanlp/plbart-javascript-en_XX | cd6ccba4322ae1156f46cd66a4cd347396e5f0c6 | 2021-11-09T17:09:03.000Z | [
"pytorch",
"plbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uclanlp | null | uclanlp/plbart-javascript-en_XX | 11 | null | transformers | 11,153 | Entry not found |
uclanlp/plbart-single_task-interpreted-summarization | 8b8b4c7eceedacbce73ce35db33581297f3cf6d0 | 2022-03-02T07:18:17.000Z | [
"pytorch",
"plbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uclanlp | null | uclanlp/plbart-single_task-interpreted-summarization | 11 | null | transformers | 11,154 | Entry not found |
unicamp-dl/ptt5-small-t5-vocab | f9b94c40e21ae3437745254f09cd05c22d9f383c | 2021-06-23T14:35:18.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"pt",
"dataset:brWaC",
"transformers",
"tensorflow",
"pt-br",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | unicamp-dl | null | unicamp-dl/ptt5-small-t5-vocab | 11 | null | transformers | 11,155 | ---
language: pt
license: mit
tags:
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- brWaC
widget:
- text: "Texto de exemplo em português"
inference: false
---
# Portuguese T5 (aka "PTT5")
## Introduction
PTT5 is a T5 model pretrained in the BrWac corpus, a large collection of web pages in Portuguese, improvi... |
usami/distilbert-base-uncased-finetuned-squad | 7789301904b54425cc675ba9d993641aff5057b9 | 2021-11-22T05:00:14.000Z | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | usami | null | usami/distilbert-base-uncased-finetuned-squad | 11 | null | transformers | 11,156 | Entry not found |
vasudevgupta/bigbird-pegasus-large-arxiv | 6c6fe12337ca6163a7c037a98c5b9014aa0ffb8b | 2021-05-04T11:12:15.000Z | [
"pytorch",
"bigbird_pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vasudevgupta | null | vasudevgupta/bigbird-pegasus-large-arxiv | 11 | null | transformers | 11,157 | Moved here: https://huggingface.co/google/bigbird-pegasus-large-arxiv |
vera-pro/bert-mention-en | 7f98a5ac4cabea8afd6e7b3bc99279d8f15a0ffe | 2021-05-20T08:54:13.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | vera-pro | null | vera-pro/bert-mention-en | 11 | null | transformers | 11,158 | Entry not found |
vera-pro/bert-mention-fr | 44540bb9306318fb86dbcda06a88a8d6f5bd3b1a | 2021-05-20T08:55:28.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | vera-pro | null | vera-pro/bert-mention-fr | 11 | null | transformers | 11,159 | Entry not found |
vesteinn/XLMR-ENIS-finetuned-ner | 2bc9cc721e44344f1453be39fada67e095160755 | 2021-09-28T20:43:19.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"en",
"is",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:agpl-3.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | vesteinn | null | vesteinn/XLMR-ENIS-finetuned-ner | 11 | 1 | transformers | 11,160 | ---
license: agpl-3.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
language:
- en
- is
model-index:
- name: XLMR-ENIS-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type:... |
vinhood/chefberto-italian-cased | 13845093331d54458b4508c66a35ead0ff7e466f | 2022-01-02T20:24:22.000Z | [
"pytorch",
"bert",
"fill-mask",
"it",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | vinhood | null | vinhood/chefberto-italian-cased | 11 | null | transformers | 11,161 | ---
language: it
license: mit
widget:
- text: "La pasta più semplice è aglio, [MASK] e peperoncino."
- text: "Per fare la carbonara servono le [MASK]."
- text: "A tavola non può mancare del buon [MASK]."
---
# ChefBERTo 👨🍳
**chefberto-italian-cased** is a BERT model obtained by MLM adaptive-tuning [**bert-base-i... |
voidful/tts_hubert_cluster_bart_base | 8975f9dcf1a9b02fa92cb6e455a9086432add72f | 2021-08-11T07:19:13.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:librispeech",
"transformers",
"audio",
"automatic-speech-recognition",
"speech",
"asr",
"hubert",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | voidful | null | voidful/tts_hubert_cluster_bart_base | 11 | null | transformers | 11,162 | ---
language: en
datasets:
- librispeech
tags:
- audio
- automatic-speech-recognition
- speech
- asr
- hubert
license: apache-2.0
metrics:
- wer
- cer
---
# voidful/tts_hubert_cluster_bart_base
## Usage
````python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained... |
yoshitomo-matsubara/bert-base-uncased-wnli_from_bert-large-uncased-wnli | e77239d25f8338eafcda2b47ad57243d8bb44061 | 2021-06-03T05:12:16.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:wnli",
"transformers",
"wnli",
"glue",
"kd",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-base-uncased-wnli_from_bert-large-uncased-wnli | 11 | null | transformers | 11,163 | ---
language: en
tags:
- bert
- wnli
- glue
- kd
- torchdistill
license: apache-2.0
datasets:
- wnli
metrics:
- accuracy
---
`bert-base-uncased` fine-tuned on WNLI dataset, using fine-tuned `bert-large-uncased` as a teacher model, [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Co... |
yoshitomo-matsubara/bert-large-uncased-stsb | 59d22c2cb70a5fae4928263c42e2f74762418a67 | 2021-05-29T21:34:30.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:stsb",
"transformers",
"stsb",
"glue",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-large-uncased-stsb | 11 | null | transformers | 11,164 | ---
language: en
tags:
- bert
- stsb
- glue
- torchdistill
license: apache-2.0
datasets:
- stsb
metrics:
- pearson correlation
- spearman correlation
---
`bert-large-uncased` fine-tuned on STS-B dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.re... |
z6228574/codegpt | 38be69baf21c2ed42e7df0c35c70369f6f1bcbaf | 2021-07-07T10:45:39.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | z6228574 | null | z6228574/codegpt | 11 | null | transformers | 11,165 | Entry not found |
zanelim/singbert-large-sg | 03a9bc840176ce94408fa77378f002e8373927a1 | 2021-05-20T09:36:17.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"pretraining",
"en",
"dataset:reddit singapore, malaysia",
"dataset:hardwarezone",
"transformers",
"singapore",
"sg",
"singlish",
"malaysia",
"ms",
"manglish",
"bert-large-uncased",
"license:mit"
] | null | false | zanelim | null | zanelim/singbert-large-sg | 11 | 1 | transformers | 11,166 | ---
language: en
tags:
- singapore
- sg
- singlish
- malaysia
- ms
- manglish
- bert-large-uncased
license: mit
datasets:
- reddit singapore, malaysia
- hardwarezone
widget:
- text: "kopi c siew [MASK]"
- text: "die [MASK] must try"
---
# Model name
SingBert Large - Bert for Singlish (SG) and Manglish (MY).
## Model... |
wietsedv/xlm-roberta-base-ft-udpos28-zh | 8191f0f4a70f7c127e222490c1b1e8e61ff4ff4d | 2022-02-25T09:59:40.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"zh",
"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-zh | 11 | null | transformers | 11,167 |
---
language:
- zh
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-zh
results:
- task:
type: token-classification
name: Part-of-Speech Tagging
datas... |
SuperAI2-Machima/mt5-small-thai-qg-v2 | ba0dfc3b8a8699fef51c7722ad84f29f9c9e80fb | 2022-03-01T14:53:52.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"thai",
"th",
"dataset:NSC2018",
"dataset:wiki-documents-nsc",
"dataset:ThaiQACorpus-DevelopmentDataset",
"transformers",
"question-generation",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | SuperAI2-Machima | null | SuperAI2-Machima/mt5-small-thai-qg-v2 | 11 | 2 | transformers | 11,168 | ---
tags:
- question-generation
language:
- thai
- th
datasets:
- NSC2018
- wiki-documents-nsc
- ThaiQACorpus-DevelopmentDataset
widget:
- text: "โรงเรียนบ้านขุนด่าน ตั้งอยู่ที่ขุนด่าน จ.นครนายก </s>"
example_title: "Example 01"
- text: "พลเอก ประยุทธ์ จันทร์โอชา (เกิด 21 มีนาคม พ.ศ. 2497) ชื่อเล่น ตู่ เป็นนักการเมื... |
mrm8488/biomedtra-small-es | e48b9360e1b3a886851a0c3fff5f07d67963a1e6 | 2022-03-30T21:07:50.000Z | [
"pytorch",
"tensorboard",
"electra",
"pretraining",
"es",
"dataset:cowese",
"transformers",
"Spanish",
"Electra",
"Bio",
"Medical"
] | null | false | mrm8488 | null | mrm8488/biomedtra-small-es | 11 | 2 | transformers | 11,169 | ---
language: es
tags:
- Spanish
- Electra
- Bio
- Medical
datasets:
- cowese
---
## 🦠 BIOMEDtra 🏥
**BIOMEDtra** (small) is an Electra like model (discriminator in this case) trained on [Spanish Biomedical Crawled Corpus](https://zenodo.org/record/5510033#.Yhdk1ZHMLJx).
As mentioned in the original [paper](h... |
inovex/multi2convai-corona-en-bert | 5e862ff6f37fe603efa642cefb4e7538ddce0898 | 2022-03-01T09:20:04.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"transformers",
"license:mit"
] | text-classification | false | inovex | null | inovex/multi2convai-corona-en-bert | 11 | null | transformers | 11,170 | ---
tags:
- text-classification
- pytorch
- transformers
widget:
- text: "Do I need to wear a mask?"
license: mit
language: en
---
# Multi2ConvAI-Corona: finetuned Bert for English
This model was developed in the [Multi2ConvAI](https://multi2conv.ai) project:
- domain: Corona (more details about our us... |
ghadeermobasher/BC5CDR-Disease-Modified_BiomedNLP-PubMedBERT-base-uncased-abstract | fa7196fb87e9f0a57b50ef596b09dcdf9f62d9b7 | 2022-02-25T18:29:23.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC5CDR-Disease-Modified_BiomedNLP-PubMedBERT-base-uncased-abstract | 11 | null | transformers | 11,171 | Entry not found |
Jackett/subject_classifier | e84d02b8f8251e1ce439d589b8fe2a15ce6cfefc | 2022-02-27T04:57:39.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | Jackett | null | Jackett/subject_classifier | 11 | null | transformers | 11,172 | Label association
{'Biology': 0, 'Physics': 1, 'Chemistry': 2, 'Maths': 3}
|
facebook/wav2vec2-base-en-voxpopuli-v2 | f464d59d152a11106e62cecb3b3bcdfd8f9d1b3f | 2022-02-27T13:13:03.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"en",
"dataset:voxpopuli",
"arxiv:2101.00390",
"transformers",
"audio",
"automatic-speech-recognition",
"voxpopuli-v2",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-en-voxpopuli-v2 | 11 | null | transformers | 11,173 | ---
language: en
tags:
- audio
- automatic-speech-recognition
- voxpopuli-v2
datasets:
- voxpopuli
license: cc-by-nc-4.0
inference: false
---
# Wav2Vec2-base-VoxPopuli-V2
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained only in **en*... |
azizbarank/mbert-finetuned-azerbaijani-ner | fbba54b7deeb4a5bcce5ca5d33f7c5f776fa084e | 2022-03-01T00:58:02.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:wikiann",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | azizbarank | null | azizbarank/mbert-finetuned-azerbaijani-ner | 11 | null | transformers | 11,174 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mbert-finetuned-azerbaijani-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
... |
coastalcph/fairlex-scotus-minilm | 2df435689d16fdcbaee9d901a122f6100d17cd1d | 2022-03-01T13:24:01.000Z | [
"pytorch",
"roberta",
"fill-mask",
"en",
"transformers",
"legal",
"fairlex",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | coastalcph | null | coastalcph/fairlex-scotus-minilm | 11 | null | transformers | 11,175 | ---
language: en
pipeline_tag: fill-mask
license: cc-by-nc-sa-4.0
tags:
- legal
- fairlex
widget:
- text: "Because the Court granted <mask> before judgment, the Court effectively stands in the shoes of the Court of Appeals and reviews the defendants’ appeals."
---
# FairLex: A multilingual benchmark for evaluating fai... |
adit94/relevancy_classifier | e8720d8fd074c4d649e276743b6675832b5b280c | 2022-03-02T06:45:18.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | adit94 | null | adit94/relevancy_classifier | 11 | null | transformers | 11,176 | {'junk': 0, 'relevant': 1}
|
segments-tobias/segformer-b3-finetuned-segments-sidewalk | c9757006e487c23728d764e475683631d7b296a8 | 2022-03-08T17:32:09.000Z | [
"pytorch",
"segformer",
"dataset:segments/sidewalk-semantic",
"transformers",
"generated_from_trainer",
"vision",
"image-segmentation",
"license:apache-2.0",
"model-index"
] | image-segmentation | false | segments-tobias | null | segments-tobias/segformer-b3-finetuned-segments-sidewalk | 11 | 1 | transformers | 11,177 | ---
license: apache-2.0
tags:
- generated_from_trainer
- vision
- image-segmentation
datasets:
- segments/sidewalk-semantic
widget:
- src: https://segmentsai-prod.s3.eu-west-2.amazonaws.com/assets/admin-tobias/439f6843-80c5-47ce-9b17-0b2a1d54dbeb.jpg
example_title: Brugge
model-index:
- name: segformer-b3-finetuned-s... |
ekohrt/qcat | 52d9238577b4e4486318b29a78f53c5f0800a04c | 2022-03-10T16:10:25.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | ekohrt | null | ekohrt/qcat | 11 | null | transformers | 11,178 | ---
license: mit
---
# **Q-Cat**
A pre-trained Distilbert model for classifying question types. For use in QA systems.
Dataset contains ~800 labeled examples. Classifier uses a taxonomy of 27 question types. |
mcdzwil/bert-base-NER-finetuned-ner-ISU | 5e003bfe8c57864e450195f429f224f4edf91160 | 2022-03-03T20:21:38.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | mcdzwil | null | mcdzwil/bert-base-NER-finetuned-ner-ISU | 11 | null | transformers | 11,179 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-NER-finetuned-ner-ISU
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... |
azaninello/distilbert-base-uncased-finetuned-mushrooms | bca1be2660863efa4061a53835d45f4540f5ef60 | 2022-03-04T17:45:46.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | azaninello | null | azaninello/distilbert-base-uncased-finetuned-mushrooms | 11 | null | transformers | 11,180 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-mushrooms
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... |
cambridgeltl/simctg_writingprompts | 2d8e8b0e47b4a70b54f19835c605e3ceff3240a2 | 2022-06-25T19:21:26.000Z | [
"pytorch",
"gpt2",
"text-generation",
"arxiv:1805.04833",
"arxiv:2202.06417",
"transformers"
] | text-generation | false | cambridgeltl | null | cambridgeltl/simctg_writingprompts | 11 | null | transformers | 11,181 | This model provides a GPT-2 language model trained with SimCTG on the WritingPrompts benchmark [(Fan et al., 2018)](https://arxiv.org/abs/1805.04833) based on our paper [_A Contrastive Framework for Neural Text Generation_](https://arxiv.org/abs/2202.06417).
We provide a detailed tutorial on how to apply SimCTG and Co... |
MrAnderson/nystrom-512-full-trivia | bda8883ec231b512572768053e0c8b592f6051d9 | 2022-03-07T21:00:48.000Z | [
"pytorch",
"nystromformer",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | MrAnderson | null | MrAnderson/nystrom-512-full-trivia | 11 | null | transformers | 11,182 | Entry not found |
StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-Concat_CRAFT_es | 41484e61f5f6d7870e2952aa8a52a7672397ab11 | 2022-03-08T10:57:12.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | StivenLancheros | null | StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-Concat_CRAFT_es | 11 | null | transformers | 11,183 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biobert-base-cased-v1.2-finetuned-ner-Concat_CRAFT_es
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... |
ICFNext/EYY-Categorisation | 6c711628fdd64a53494eb4d4be51fe17f2445412 | 2022-03-12T13:24:28.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | ICFNext | null | ICFNext/EYY-Categorisation | 11 | 0 | transformers | 11,184 | |
antho-data/distilbert-base-uncased-finetuned-emotion | 739aae9e1e6991556d1c3a6feed4a9957e256e5f | 2022-03-09T21:27:17.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | antho-data | null | antho-data/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,185 | ---
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... |
farrokhguiahi/distilbert-base-uncased-finetuned-emotion | 040434f3bbe596ecfbe811e02b7102da6bb6546f | 2022-03-28T15:19:47.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | farrokhguiahi | null | farrokhguiahi/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,186 | ---
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... |
waboucay/camembert-base-finetuned-xnli_fr | 9a935237b3054740cb4ef28092f3e83999392940 | 2022-03-30T17:47:05.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"transformers",
"nli"
] | text-classification | false | waboucay | null | waboucay/camembert-base-finetuned-xnli_fr | 11 | null | transformers | 11,187 | ---
language:
- fr
tags:
- nli
metrics:
- f1
---
## Eval results
We obtain the following results on ```validation``` and ```test``` sets:
| Set | F1<sub>micro</sub> | F1<sub>macro</sub> |
|------------|--------------------|--------------------|
| validation | 89.2 | 87.6 |
| test ... |
markt23917/finetuning-sentiment-model-3000-samples | a8a92d619d3ac84f1ddca70304060f5a50e4d85f | 2022-03-12T08:11:37.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | markt23917 | null | markt23917/finetuning-sentiment-model-3000-samples | 11 | null | transformers | 11,188 | ---
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... |
MrAnderson/yoso-512-full-trivia-copied-embeddings | 36119b9255ccc138a76c4cff5ee749515408782d | 2022-03-13T15:24:35.000Z | [
"pytorch",
"yoso",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | MrAnderson | null | MrAnderson/yoso-512-full-trivia-copied-embeddings | 11 | null | transformers | 11,189 | Entry not found |
DrishtiSharma/autonlp-Text-Classification-Catalonia-Independence-AutoNLP-633018323 | 5cc52158825e20033c8be795a573910026a53f1a | 2022-03-13T07:31:45.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:DrishtiSharma/autonlp-data-Text-Classification-Catalonia-Independence-AutoNLP",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | false | DrishtiSharma | null | DrishtiSharma/autonlp-Text-Classification-Catalonia-Independence-AutoNLP-633018323 | 11 | null | transformers | 11,190 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- DrishtiSharma/autonlp-data-Text-Classification-Catalonia-Independence-AutoNLP
co2_eq_emissions: 3.622203603306694
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 633018323
- CO2 Emissions (in grams)... |
anwesham/mbert_ar_ur | 2daa617f0a9e3acc6112eb553a077a95727c20ae | 2022-03-13T10:10:05.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | anwesham | null | anwesham/mbert_ar_ur | 11 | null | transformers | 11,191 | Entry not found |
lanesket/finetuned-r-codebert-mlm | 1c9c4e0cea102c7ecf44cc2de0ecf9182c209f54 | 2022-03-30T11:45:55.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | lanesket | null | lanesket/finetuned-r-codebert-mlm | 11 | null | transformers | 11,192 | Entry not found |
jfealko/wav2vec2-large-xls-r-300m-irish-wav-dataset | 6fae06e9fef0bbb7e1b3c769afc0c102d049d694 | 2022-03-14T02:29:26.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | jfealko | null | jfealko/wav2vec2-large-xls-r-300m-irish-wav-dataset | 11 | null | transformers | 11,193 | Entry not found |
quincyqiang/distilbert-base-uncased-finetuned-emotion | 4ad4db56c7181bf32997dff379f9279add872f05 | 2022-07-21T08:11:11.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | quincyqiang | null | quincyqiang/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,194 | ---
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... |
anton-l/xtreme_s_xlsr_bart_covost | 4cbfc360b01f25af319f1d36db6a7a52cdc19001 | 2022-03-15T14:31:12.000Z | [
"pytorch",
"tensorboard",
"speech-encoder-decoder",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | false | anton-l | null | anton-l/xtreme_s_xlsr_bart_covost | 11 | null | transformers | 11,195 | Entry not found |
moralstories/roberta-large_action-norm | b40b9e108a6ebe0df18e2e236c4df9b629c616cd | 2022-03-15T17:35:54.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"license:afl-3.0"
] | text-classification | false | moralstories | null | moralstories/roberta-large_action-norm | 11 | null | transformers | 11,196 | ---
license: afl-3.0
---
|
dodobird/distilbert-base-uncased-finetuned-emotion | fc9b0213ab130bae696508ad981c6fcc02d6bba0 | 2022-03-21T03:04:10.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | dodobird | null | dodobird/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,197 | ---
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... |
rurupang/bert-base-finetuned-sts | 9d3f592604aec5277771e0d35d6da18baedfc198 | 2022-03-21T19:23:42.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:klue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | rurupang | null | rurupang/bert-base-finetuned-sts | 11 | null | transformers | 11,198 | ---
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- pearsonr
model-index:
- name: bert-base-finetuned-sts
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: klue
type: klue
args: sts
metrics:
- name: Pearsonr
type: pearsonr
... |
loulou/distilbert-base-uncased-finetuned-emotion | 207b288ea8133de25e4b8bf5bf168e3d6c6f5ea4 | 2022-03-30T04:57:58.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | loulou | null | loulou/distilbert-base-uncased-finetuned-emotion | 11 | null | transformers | 11,199 | ---
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... |
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