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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
sadakmed/distiluse-base-multilingual-cased-v1 | 2c2289a5bd6c89505c77d6b2ca7d1a7a56b2b106 | 2021-09-22T09:37:18.000Z | [
"pytorch",
"multilingual",
"sentence-transformers",
"DistilBert",
"Universal Sentence Encoder",
"sentence-embeddings",
"sentence-similarity",
"license:apache-2.0"
] | sentence-similarity | false | sadakmed | null | sadakmed/distiluse-base-multilingual-cased-v1 | 41 | null | sentence-transformers | 6,400 | ---
language: multilingual
tags:
- DistilBert
- Universal Sentence Encoder
- sentence-embeddings
- sentence-transformers
- sentence-similarity
license: apache-2.0
---
Knowledge distilled version of multilingual Universal Sentence Encoder. Supports 15 languages: Arabic, Chinese, Dutch, English, French, German, Italian, ... |
snisioi/bert-legal-romanian-cased-v1 | 49fa6ad60b74ce898c75a81fb5f77d8f84e2a837 | 2022-01-17T20:32:58.000Z | [
"pytorch",
"bert",
"text-generation",
"transformers"
] | text-generation | false | snisioi | null | snisioi/bert-legal-romanian-cased-v1 | 41 | null | transformers | 6,401 | A Romanian BERT model, initialized from [bert-base-romanian-cased-v1](https://huggingface.co/dumitrescustefan/bert-base-romanian-cased-v1) and pretrained on the [MARCELL v2.0 corpus](https://elrc-share.eu/repository/browse/marcell-romanian-legislative-subcorpus-v2/2da548428b9d11eb9c1a00155d026706ce94a6b59ffc4b0e9fb5cd9... |
tcaputi/guns-relevant | f97fd7332c0ff78a4f2334a8e850b64c7a0211dd | 2021-05-20T07:25:33.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | tcaputi | null | tcaputi/guns-relevant | 41 | null | transformers | 6,402 | Entry not found |
vesteinn/XLMR-ENIS-finetuned-cola | df5e8c202b8c76982ec78efeed84f31a63ca467a | 2021-09-27T22:07:58.000Z | [
"pytorch",
"tensorboard",
"xlm-roberta",
"text-classification",
"en",
"is",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:agpl-3.0",
"model-index"
] | text-classification | false | vesteinn | null | vesteinn/XLMR-ENIS-finetuned-cola | 41 | null | transformers | 6,403 | ---
license: agpl-3.0
tags:
- generated_from_trainer
datasets:
- glue
language:
- en
- is
metrics:
- matthews_correlation
model-index:
- name: XLMR-ENIS-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
... |
bookbot/distil-wav2vec2-xls-r-adult-child-cls-64m | 99a11467d83a54b5146556b9d71638c161dd17ba | 2022-02-26T14:40:27.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"en",
"arxiv:2111.09296",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | bookbot | null | bookbot/distil-wav2vec2-xls-r-adult-child-cls-64m | 41 | null | transformers | 6,404 | ---
language: en
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distil-wav2vec2-xls-r-adult-child-cls-64m
results: []
---
# DistilWav2Vec2 XLS-R Adult/Child Speech Classifier 64M
DistilWav2Vec2 XLS-R Adult/Child Speech Classifier i... |
MLRS/mBERTu | cd6fcd6144de0b73477fb1e17ba3f51a09ba8152 | 2022-05-20T17:30:19.000Z | [
"pytorch",
"bert",
"fill-mask",
"mt",
"dataset:MLRS/korpus_malti",
"arxiv:2205.10517",
"transformers",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | MLRS | null | MLRS/mBERTu | 41 | null | transformers | 6,405 | ---
language:
- mt
datasets:
- MLRS/korpus_malti
model-index:
- name: mBERTu
results:
- task:
type: dependency-parsing
name: Dependency Parsing
dataset:
type: universal_dependencies
args: mt_mudt
name: Maltese Universal Dependencies Treebank (MUDT)
metrics:
- type: uas
... |
nbhimte/tiny-bert-mnli-distilled | 730f7a5e90fa201750e27cd5491e8100495845ad | 2022-05-04T07:14:17.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | nbhimte | null | nbhimte/tiny-bert-mnli-distilled | 41 | null | transformers | 6,406 | ---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny-bert-mnli-distilled
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: mnli
metrics:
- name: Accuracy
type: accurac... |
anshr/distilgpt2_supervised_model_01 | 521275113c0e94685be02ffc8471b8b60f5bc990 | 2022-04-24T00:33:40.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | anshr | null | anshr/distilgpt2_supervised_model_01 | 41 | null | transformers | 6,407 | Entry not found |
Yanhao/simcse-bert-for-patent | e46b5526806e0a2cc868ea06ffff6e113fb62a20 | 2022-05-04T21:32:00.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | Yanhao | null | Yanhao/simcse-bert-for-patent | 41 | 1 | transformers | 6,408 | Entry not found |
CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_42 | 58c38e89c8ca126a5082a7caa9dd0f951258bcd6 | 2022-05-10T23:21:14.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | CEBaB | null | CEBaB/bert-base-uncased.CEBaB.sa.2-class.exclusive.seed_42 | 41 | null | transformers | 6,409 | Entry not found |
erickfm/t5-base-finetuned-bias | d18b5a444ca6a641921a78c34093e576aa966d38 | 2022-06-01T18:28:29.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:WNC",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | erickfm | null | erickfm/t5-base-finetuned-bias | 41 | null | transformers | 6,410 | ---
language:
- en
license: apache-2.0
datasets:
- WNC
metrics:
- accuracy
---
This model is a fine-tune checkpoint of [T5-base](https://huggingface.co/t5-base), fine-tuned on the [Wiki Neutrality Corpus (WNC)](https://github.com/rpryzant/neutralizing-bias), a labeled dataset composed of 180,000 biased and neutrali... |
cambridgeltl/tweet-roberta-base-embeddings-v1 | de1dc3f55e55d54f784c669a30f6edf81ba08d49 | 2022-06-06T14:23:18.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"transformers",
"license:afl-3.0"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/tweet-roberta-base-embeddings-v1 | 41 | null | transformers | 6,411 | ---
license: afl-3.0
---
|
waboucay/camembert-large-finetuned-xnli_fr_3_classes | 534cf93a172b82e7b948e9f48d6640aea1fb3bd3 | 2022-06-19T14:38:51.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"transformers",
"nli"
] | text-classification | false | waboucay | null | waboucay/camembert-large-finetuned-xnli_fr_3_classes | 41 | null | transformers | 6,412 | ---
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 | 85.8 | 85.9 |
| test ... |
vaibhavagg303/Pegasus-Large | e041bcd9795d321ff092ffb9642034b83970071d | 2022-06-29T15:30:27.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vaibhavagg303 | null | vaibhavagg303/Pegasus-Large | 41 | null | transformers | 6,413 | Entry not found |
ychenNLP/arabic-relation-extraction | a66d4eebf771dcb7e0d477943d8f54ab561acfdc | 2022-07-10T18:47:45.000Z | [
"pytorch",
"tf",
"tensorboard",
"bert",
"text-classification",
"ar",
"en",
"dataset:ACE2005",
"transformers",
"BERT",
"Text Classification",
"relation",
"license:mit"
] | text-classification | false | ychenNLP | null | ychenNLP/arabic-relation-extraction | 41 | 1 | transformers | 6,414 | ---
tags:
- BERT
- Text Classification
- relation
language:
- ar
- en
license: mit
datasets:
- ACE2005
---
# Arabic Relation Extraction Model
- [Github repo](https://github.com/edchengg/GigaBERT)
- Relation Extraction model based on [GigaBERTv4](https://huggingface.co/lanwuwei/GigaBERT-v4-Arabic-and-English).
- Model ... |
Talha/urdu-audio-emotions | 89fb626253dca39fa0334f7a36cebf895e6e4e0c | 2022-07-02T11:04:29.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"audio-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | Talha | null | Talha/urdu-audio-emotions | 41 | 1 | transformers | 6,415 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
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. -->
# results... |
datien228/distilbart-ftn-wiki_lingua | 3f7f4c27a0e1550bb01571aadf1946405bbda52d | 2022-07-05T12:12:07.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:wiki_lingua",
"transformers",
"summarization",
"license:mit",
"autotrain_compatible"
] | summarization | false | datien228 | null | datien228/distilbart-ftn-wiki_lingua | 41 | null | transformers | 6,416 | ---
language:
- en
tags:
- summarization
license: mit
datasets:
- wiki_lingua
metrics:
- rouge
---
#### Pre-trained BART Model fine-tune on WikiLingua dataset
The repository for the fine-tuned BART model (by sshleifer) using the **wiki_lingua** dataset (English)
**Purpose:** Examine the performance of a fine-tuned mo... |
cambridgeltl/simctg_cnwikitext | f9d6161e94e5d3cefb87911307c7320a107b93a3 | 2022-07-03T20:44:52.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | cambridgeltl | null | cambridgeltl/simctg_cnwikitext | 41 | null | transformers | 6,417 | Entry not found |
nakamura196/roberta-small-hi-char | 5e04e68b8f96846486af357e356a2fa5cd8b1f2c | 2022-07-14T20:32:40.000Z | [
"pytorch",
"roberta",
"fill-mask",
"ja",
"transformers",
"japanese",
"masked-lm",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | nakamura196 | null | nakamura196/roberta-small-hi-char | 41 | null | transformers | 6,418 | ---
language:
- "ja"
tags:
- "japanese"
- "masked-lm"
license: "cc-by-sa-4.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
widget:
- text: "入[MASK]外無之候江戸大水又ハ大地震なと"
- text: "日向[MASK]御望之由可令披露候"
---
# roberta-small-hi-char
## Model Description
This is a RoBERTa model pre-trained on HI texts with character tokenizer.
... |
robingeibel/reformer-finetuned-big_patent-16384 | 229f24c58abe50cbce42a408f2771dccd3a87bba | 2022-07-15T17:20:21.000Z | [
"pytorch",
"tensorboard",
"reformer",
"fill-mask",
"dataset:big_patent",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | robingeibel | null | robingeibel/reformer-finetuned-big_patent-16384 | 41 | null | transformers | 6,419 | ---
tags:
- generated_from_trainer
datasets:
- big_patent
model-index:
- name: reformer-finetuned-big_patent-16384
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. -->... |
ArthurBaia/xlm-roberta-base-squad-pt | a3fd9b3c344b480e991c66bd0fa5f7d59b0e9ca5 | 2022-07-11T22:42:37.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"dataset:squad_v1_pt",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | question-answering | false | ArthurBaia | null | ArthurBaia/xlm-roberta-base-squad-pt | 41 | 1 | transformers | 6,420 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v1_pt
model-index:
- name: xlm-roberta-base-squad-pt
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.... |
finiteautomata/definition-ner | 197175a16e419b7442ddb9f090e3eabf2c226eec | 2022-07-13T01:51:40.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | finiteautomata | null | finiteautomata/definition-ner | 41 | null | transformers | 6,421 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: definition-ner
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 co... |
baptiste/deberta-finetuned-ner | 75f2bdd20e3bd03fe16c24c692d6e8cb3c2163d2 | 2022-07-16T05:46:56.000Z | [
"pytorch",
"tensorboard",
"deberta",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | baptiste | null | baptiste/deberta-finetuned-ner | 41 | null | transformers | 6,422 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll... |
Aimlab/xlm-roberta-base-finetuned-urdu | 9fd928480ae7b6bcc5bce9c0efe0e2897116839e | 2022-07-25T07:58:10.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ur",
"transformers",
"license:afl-3.0"
] | text-classification | false | Aimlab | null | Aimlab/xlm-roberta-base-finetuned-urdu | 41 | 1 | transformers | 6,423 | ---
language: ur
license: afl-3.0
---
# XLM-RoBERTa-Urdu-Classification
This [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) text classification model trained on Urdu sentiment [data-set](https://huggingface.co/datasets/hassan4830/urdu-binary-classification-data) performs binary sentiment classification ... |
asi/igpt-fr-cased-base | 75771e2d79a2fc86e91c487b6766ee639fb48d3e | 2022-07-27T17:12:36.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"fr",
"transformers",
"tf",
"text-to-image",
"license:apache-2.0"
] | text-generation | false | asi | null | asi/igpt-fr-cased-base | 41 | 2 | transformers | 6,424 | ---
language:
- fr
thumbnail: https://raw.githubusercontent.com/AntoineSimoulin/gpt-fr/main/imgs/logo.png
tags:
- tf
- pytorch
- gpt2
- text-to-image
license: apache-2.0
---
<img src="https://raw.githubusercontent.com/AntoineSimoulin/gpt-fr/main/imgs/igpt-logo.png" width="400">
## Model description
**iGPT-fr** 🇫�... |
NLPScholars/Roberta-Earning-Call-Transcript-Classification | b2a2f9acea1ffb73453a8361960c35215cf16f77 | 2022-07-29T15:38:27.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | NLPScholars | null | NLPScholars/Roberta-Earning-Call-Transcript-Classification | 41 | 1 | transformers | 6,425 | ---
widget:
- text: "Paytm’s Revenue Growth Trajectory To Remain Strong In Q1: Goldman Sachs"
- text: "Nifty ends above 16,900, Sensex gains 1,041 pts led by IT, metal, realty"
- text: "Amazon reports BLOWOUT earnings, beating revenue estimates and raising Q3 guidance"
- text: "Company went through great loss due to la... |
Fujitsu/pytorrent | 1bf2dc4833d0cc0dc3020c0a36364aafc54694f1 | 2021-10-12T18:37:18.000Z | [
"pytorch",
"jax",
"roberta",
"feature-extraction",
"en",
"dataset:pytorrent",
"arxiv:2110.01710",
"transformers",
"license:mit"
] | feature-extraction | false | Fujitsu | null | Fujitsu/pytorrent | 40 | null | transformers | 6,426 | ---
license: mit
widget:
language:
- en
datasets:
- pytorrent
---
# 🔥 RoBERTa-MLM-based PyTorrent 1M 🔥
Pretrained weights based on [PyTorrent Dataset](https://github.com/fla-sil/PyTorrent) which is a curated data from a large official Python packages.
We use PyTorrent dataset to train a preliminary DistilBERT-Mask... |
Helsinki-NLP/opus-mt-de-eo | 9188e5326cba934d553fcb0150a9e88de140a286 | 2021-09-09T21:30:54.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"eo",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-eo | 40 | null | transformers | 6,427 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-de-eo
* source languages: de
* target languages: eo
* OPUS readme: [de-eo](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-eo/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-en-ceb | a5e0a21b4e9db37945be9cd5977573b53cd95999 | 2021-09-09T21:34:30.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ceb",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ceb | 40 | null | transformers | 6,428 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ceb
* source languages: en
* target languages: ceb
* OPUS readme: [en-ceb](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-ceb/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-en-ilo | 7342bf73c00ab920930c2f25166e0521a32f9048 | 2021-09-09T21:36:15.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"ilo",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-ilo | 40 | null | transformers | 6,429 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-ilo
* source languages: en
* target languages: ilo
* OPUS readme: [en-ilo](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-ilo/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-en-xh | 7cd68494528d1a3fe8f726fb0cf3713e448b70a4 | 2021-09-09T21:40:37.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"xh",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-xh | 40 | null | transformers | 6,430 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-xh
* source languages: en
* target languages: xh
* OPUS readme: [en-xh](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-xh/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-nso-en | 4c49083b63f01ac0a3b32a81ade912d4f1367948 | 2021-09-10T13:59:30.000Z | [
"pytorch",
"marian",
"text2text-generation",
"nso",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-nso-en | 40 | null | transformers | 6,431 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-nso-en
* source languages: nso
* target languages: en
* OPUS readme: [nso-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/nso-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Narrativa/byt5-base-finetuned-tweet-qa | 5b01a203964d7a8d81c31475610732ff749bcbd1 | 2021-06-30T14:55:05.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:tweet_qa",
"arxiv:1907.06292",
"arxiv:1910.10683",
"transformers",
"qa",
"Question Answering",
"autotrain_compatible"
] | text2text-generation | false | Narrativa | null | Narrativa/byt5-base-finetuned-tweet-qa | 40 | null | transformers | 6,432 | ---
language: en
datasets:
- tweet_qa
tags:
- qa
- Question Answering
widget:
- text: "question: how far away was the putt context: GET THE CIGAR READY! Miguel aces the 15th from 174 yards, and celebrates as only he knows how! The European Tour (@EuropeanTour) January, 15 2015"
---
# ByT5-base fine-tuned for Questio... |
Narrativa/spanish-gpt2-finetuned-rap-lyrics | 3447ebcd3d4592df8c525c4c9b303c11fa4c1735 | 2021-09-11T08:46:33.000Z | [
"pytorch",
"gpt2",
"text-generation",
"es",
"dataset:large_spanish_corpus",
"transformers",
"GPT-2",
"Rap",
"Lyrics",
"Songs",
"license:mit"
] | text-generation | false | Narrativa | null | Narrativa/spanish-gpt2-finetuned-rap-lyrics | 40 | 3 | transformers | 6,433 | ---
language: es
tags:
- GPT-2
- Rap
- Lyrics
- Songs
datasets:
- large_spanish_corpus
widget:
- text: "Déjame contarte lo importante que es buscarte un plan\nNo para golpearles o ganarles, sino para darles paz\n"
license: mit
---
# Spanish GPT-2 trained on [Spanish RAP Lyrics](https://www.kaggle.com/smunoz3801/9325... |
NbAiLab/nb-t5-base | 73ebe153a4543ebef6449c70f3b1f3190208139c | 2021-09-23T15:53:02.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"no",
"dataset:Norwegian Nynorsk/Bokmål",
"transformers",
"seq2seq",
"license:cc-by-4.0"
] | feature-extraction | false | NbAiLab | null | NbAiLab/nb-t5-base | 40 | 2 | transformers | 6,434 | ---
language: no
license: cc-by-4.0
tags:
- seq2seq
datasets:
- Norwegian Nynorsk/Bokmål
---
# 🇳🇴 Norwegian T5 Base model Trained on the NCC🇳🇴
This is a Norwegian T5-base model trained on the Norwegian Colossal Corpus (NCC) on a TPU v3-8. It needs to be finetuned on a specific task before being used for anything... |
Salesforce/qaconv-bert-large-uncased-whole-word-masking-squad2 | 48552b4258b70a1f007efb9d01877fe88adbe22b | 2021-05-27T19:15:05.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | Salesforce | null | Salesforce/qaconv-bert-large-uncased-whole-word-masking-squad2 | 40 | null | transformers | 6,435 | Entry not found |
alireza7/ARMAN-MSR-persian-base | be651ea4fbace219818c4958f37cb85a2a801291 | 2021-09-29T19:17:50.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | alireza7 | null | alireza7/ARMAN-MSR-persian-base | 40 | null | transformers | 6,436 | More information about models is available [here](https://github.com/alirezasalemi7/ARMAN). |
ankitkhowal/minutes-of-meeting | 359cda32c1112823f9ec08f568c78062727b14fc | 2022-03-09T18:08:01.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | ankitkhowal | null | ankitkhowal/minutes-of-meeting | 40 | null | transformers | 6,437 | Model to summarize the meeting transcripts. |
any0019/text_style_classifier | e0aa348f627e207319e7c684ffdb4e05cb1f3ac9 | 2021-12-14T13:35:07.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | any0019 | null | any0019/text_style_classifier | 40 | null | transformers | 6,438 | Entry not found |
bertin-project/bertin-base-gaussian | fea8231d1b0dab3b5ab5d9157e36935d2685e197 | 2021-09-23T13:41:46.000Z | [
"pytorch",
"jax",
"tensorboard",
"joblib",
"roberta",
"fill-mask",
"es",
"transformers",
"spanish",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | bertin-project | null | bertin-project/bertin-base-gaussian | 40 | null | transformers | 6,439 | ---
language: es
license: cc-by-4.0
tags:
- spanish
- roberta
pipeline_tag: fill-mask
widget:
- text: Fui a la librería a comprar un <mask>.
---
This is a **RoBERTa-base** model trained from scratch in Spanish.
The training dataset is [mc4](https://huggingface.co/datasets/bertin-project/mc4-es-sampled ) subsampling d... |
cardiffnlp/twitter-roberta-base-jun2020 | c961f32a31e1ba8674577c10bcbcbb0f51ab975a | 2022-02-09T11:14:02.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-jun2020 | 40 | null | transformers | 6,440 | # Twitter June 2020 (RoBERTa-base, 99M)
This is a RoBERTa-base model trained on 98.66M tweets until the end of June 2020.
More details and performance scores are available in the [TimeLMs paper](https://arxiv.org/abs/2202.03829).
Below, we provide some usage examples using the standard Transformers interface. For ano... |
dadada/opus-mt-zh-en-ep1-renri-zh-to-en | e6c208e18c39a3149fccfd87fffe0ca3477f0c67 | 2021-08-22T06:54:09.000Z | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | dadada | null | dadada/opus-mt-zh-en-ep1-renri-zh-to-en | 40 | null | transformers | 6,441 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model_index:
- name: opus-mt-zh-en-ep1-renri-zh-to-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
metric:
name: Bleu
type: bleu
value: 18.2579
---
<!-- This model ca... |
elozano/tweet_offensive_eval | 36e34e4a6c0f9cb628af3b481c8d95dfe4d1fc3f | 2022-02-07T17:59:03.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:tweet_eval",
"transformers",
"license:mit"
] | text-classification | false | elozano | null | elozano/tweet_offensive_eval | 40 | 2 | transformers | 6,442 | ---
license: mit
datasets:
- tweet_eval
language: en
widget:
- text: "You're a complete idiot!"
example_title: "Offensive"
- text: "I am tired of studying for tomorrow's exam"
example_title: "Non-Offensive"
---
|
flax-community/swe-gpt-wiki | 5141a894196173cbee58fbecf1936dd6660a35c0 | 2021-07-17T07:46:24.000Z | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"sv",
"transformers"
] | text-generation | false | flax-community | null | flax-community/swe-gpt-wiki | 40 | 1 | transformers | 6,443 | ---
language: sv
widget:
- text: "Jag är en svensk språkmodell."
---
# GPT2-svenska-wikipedia
A swedish GPT2 style model trained using Flax CLM pipeline on the Swedish
part of the wiki40b dataset.
https://huggingface.co/datasets/wiki40b
## Model series
This model is part of a series of models training on TPU with Fl... |
google/t5-efficient-xl-nl16 | 2c27584bfd88690ebb930dc31e81d3791ef7b91f | 2022-02-15T10:57:40.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"arxiv:2109.10686",
"transformers",
"deep-narrow",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-efficient-xl-nl16 | 40 | 0 | transformers | 6,444 | ---
language:
- en
datasets:
- c4
tags:
- deep-narrow
inference: false
license: apache-2.0
---
# T5-Efficient-XL-NL16 (Deep-Narrow version)
T5-Efficient-XL-NL16 is a variation of [Google's original T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) following the [T5 model architecture](h... |
helboukkouri/character-bert | 7fd0716432001b0b67a001db1c596edc213a835c | 2021-05-17T10:40:43.000Z | [
"pytorch",
"character_bert",
"transformers"
] | null | false | helboukkouri | null | helboukkouri/character-bert | 40 | 1 | transformers | 6,445 | Entry not found |
huggingtweets/empathywarrior | 758c75ea347cdfa99ebd8184a02148df56244658 | 2021-05-22T03:06:23.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/empathywarrior | 40 | null | transformers | 6,446 | ---
language: en
thumbnail: https://www.huggingtweets.com/empathywarrior/1616731099747/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1367656161... |
huggingtweets/heartswellzz | ff28400d302c35bf5d986544b9f90c24d2710d27 | 2021-05-22T06:43:16.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/heartswellzz | 40 | null | transformers | 6,447 | ---
language: en
thumbnail: https://www.huggingtweets.com/heartswellzz/1616679682815/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/126493255533... |
huggingtweets/nickjfuentes | 8bb58125c047d85837a849c8fb34b7a42dcfcb4e | 2021-05-22T16:19:55.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/nickjfuentes | 40 | null | transformers | 6,448 | ---
language: en
thumbnail: https://www.huggingtweets.com/nickjfuentes/1603507476320/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
<style>
@media (prefers-color-scheme: dark) {
.prose { c... |
leduytan93/Fine-Tune-XLSR-Wav2Vec2-Speech2Text-Vietnamese | 67e3051208e7188148ac71f791ae96e5874e6d86 | 2021-07-06T09:51:23.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"transformers",
"language-modeling",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | leduytan93 | null | leduytan93/Fine-Tune-XLSR-Wav2Vec2-Speech2Text-Vietnamese | 40 | null | transformers | 6,449 | ---
language: vi
datasets:
- common_voice
- FOSD: https://data.mendeley.com/datasets/k9sxg2twv4/4
metrics:
- wer
tags:
- language-modeling
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: MT5 Fix Asr Vietnamese by Ontocord
results:
- task:
name:... |
m3hrdadfi/albert-fa-base-v2-sentiment-multi | 15abc2f4ede4d3571e21b2b65c1383ec1a50fae8 | 2020-12-26T08:46:20.000Z | [
"pytorch",
"tf",
"albert",
"text-classification",
"fa",
"transformers",
"license:apache-2.0"
] | text-classification | false | m3hrdadfi | null | m3hrdadfi/albert-fa-base-v2-sentiment-multi | 40 | null | transformers | 6,450 | ---
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/gpt2-persian-qa | b7ce36e9ae4d841bdb0f4b559fff47e8ec4aaeb5 | 2021-07-30T09:00:42.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"fa",
"dataset:persian_qa",
"dataset:parsinlu_reading_comprehension",
"transformers"
] | text-generation | false | m3hrdadfi | null | m3hrdadfi/gpt2-persian-qa | 40 | null | transformers | 6,451 | ---
language: fa
datasets:
- persian_qa
- parsinlu_reading_comprehension
tags:
- text-generation
widget:
- text: "قرارداد کرسنت قراردادی برای فروش روزانه معادل 500 میلیون فوت مکعب، گاز ترش میدان سلمان است، که در سال 1381 و در زمان وزارت بیژن نامدار زنگنه در دولت هفتم مابین شرکت کرسنت پترولیوم و شرکت ملی نفت ایران منعق... |
meghanabhange/Hinglish-DistilBert | 16200381e14a51d090e9095cead77c5dea305f5f | 2020-10-21T12:46:32.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | meghanabhange | null | meghanabhange/Hinglish-DistilBert | 40 | null | transformers | 6,452 | Entry not found |
mrm8488/distiluse-base-multilingual-cased-v2-finetuned-stsb_multi_mt-es | f292c3eb72b2a7a4074d14541ad86320fa643e64 | 2022-02-09T13:39:25.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"es",
"dataset:stsb_multi_mt",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | mrm8488 | null | mrm8488/distiluse-base-multilingual-cased-v2-finetuned-stsb_multi_mt-es | 40 | 1 | sentence-transformers | 6,453 | ---
language: es
thumbnail: https://imgur.com/a/G77ZqQN
pipeline_tag: sentence-similarity
datasets:
- stsb_multi_mt
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# Distiluse-m-v2 fine-tuned on stsb_multi_mt for Spanish Semantic Textual Similarity
This is a [sentence-trans... |
mrm8488/t5-small-finetuned-text2log | 8a1cc5d2cfb22837838824f46147c0eeffaf3acc | 2022-02-23T18:30:38.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"en",
"transformers",
"generated_from_trainer",
"tex2log",
"log2tex",
"foc",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-small-finetuned-text2log | 40 | 1 | transformers | 6,454 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- tex2log
- log2tex
- foc
widget:
- text: "translate to nl: all x1.(_explanation(x1) -> -_equal(x1))"
- text: "translate to fol: All chains are bad."
model-index:
- name: t5-small-text2log
results: []
---
<!-- This model card has been generated ... |
oskrmiguel/mt5-simplification-spanish | 0b78e767ac9bf700152ba5a9761f09a69343a552 | 2022-01-27T13:32:24.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"es",
"transformers",
"simplification",
"spanish",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | oskrmiguel | null | oskrmiguel/mt5-simplification-spanish | 40 | 4 | transformers | 6,455 |
---
language:
- es
thumbnail:
tags:
- simplification
- mt5
- spanish
license: cc-by-nc-sa-4.0
metrics:
- sari
widget:
- text: "La Simplificación Textual es el proceso de transformación de un texto a otro texto equivalente más comprensible para un determinado tipo de grupo o población."
- text: "Los textos simplifica... |
shrugging-grace/tweetclassifier | e584ba8282d48af1f1cb0247e7a551b751ed7365 | 2021-05-20T05:55:16.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | shrugging-grace | null | shrugging-grace/tweetclassifier | 40 | null | transformers | 6,456 | # shrugging-grace/tweetclassifier
## Model description
This model classifies tweets as either relating to the Covid-19 pandemic or not.
## Intended uses & limitations
It is intended to be used on tweets commenting on UK politics, in particular those trending with the #PMQs hashtag, as this refers to weekly Prime Min... |
sibt-rj/albert-large-urdu | 997d0507940940ecbb6af536daeb1f4e1b27754e | 2020-12-16T20:27:42.000Z | [
"pytorch",
"albert",
"fill-mask",
"ur",
"dataset:urdu-text-news",
"transformers",
"urdu",
"language-model",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | sibt-rj | null | sibt-rj/albert-large-urdu | 40 | null | transformers | 6,457 | ---
language:
- ur
tags:
- urdu
- language-model
license: mit
datasets:
- urdu-text-news
---
|
tennessejoyce/titlewave-bert-base-uncased | a8d7b656a3058cceefa99dc51cf3e01fdf209ebe | 2021-05-20T07:29:09.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"en",
"transformers",
"license:cc-by-4.0"
] | text-classification | false | tennessejoyce | null | tennessejoyce/titlewave-bert-base-uncased | 40 | null | transformers | 6,458 | ---
language: en
license: cc-by-4.0
widget:
- text: "[Gmail API] How can I extract plain text from an email sent to me?"
---
# Titlewave: bert-base-uncased
## Model description
Titlewave is a Chrome extension that helps you choose better titles for your Stack Overflow questions. See the [github repository](https://g... |
uer/chinese_roberta_L-8_H-256 | c3e6cb43e6908a7cf43de4ea5a20b8fd28d84981 | 2022-07-15T08:14:03.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-8_H-256 | 40 | null | transformers | 6,459 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
unideeplearning/polibert_sa | 9f191fddcab67467555d22cebe8f88a1a908867a | 2021-09-23T16:42:31.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"it",
"transformers",
"sentiment",
"Italian",
"license:mit"
] | text-classification | false | unideeplearning | null | unideeplearning/polibert_sa | 40 | null | transformers | 6,460 | ---
language: it
tags:
- sentiment
- Italian
license: mit
widget:
- text: Giuseppe Rossi è un ottimo politico
---
# 🤗 + polibert_SA - POLItic BERT based Sentiment Analysis
## Model description
This model performs sentiment analysis on Italian political twitter sentences. It was trained starting from an instan... |
sanchit-gandhi/wav2vec2-gpt2-wandb-grid-search | f2f66e759c9dc110e409c1d75eea893c400b8248 | 2022-03-03T13:39:57.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"dataset:librispeech_asr",
"transformers",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | sanchit-gandhi | null | sanchit-gandhi/wav2vec2-gpt2-wandb-grid-search | 40 | null | transformers | 6,461 | ---
tags:
- generated_from_trainer
datasets:
- librispeech_asr
model-index:
- name: ''
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
#
This model was trained... |
batterydata/batteryscibert-uncased-abstract | 1eca2bfd6e213253a958e71707048fc4ee20625f | 2022-03-05T14:54:59.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:batterydata/paper-abstracts",
"transformers",
"Text Classification",
"license:apache-2.0"
] | text-classification | false | batterydata | null | batterydata/batteryscibert-uncased-abstract | 40 | null | transformers | 6,462 | ---
language: en
tags: Text Classification
license: apache-2.0
datasets:
- batterydata/paper-abstracts
metrics: glue
---
# BatterySciBERT-uncased for Battery Abstract Classification
**Language model:** batteryscibert-uncased
**Language:** English
**Downstream-task:** Text Classification
**Training dat... |
armageddon/albert-squad-v2-covid-qa-deepset | afcd01d73da4acba7c3ed433138fe8b84a5ff9e0 | 2022-03-01T02:04:26.000Z | [
"pytorch",
"tensorboard",
"albert",
"question-answering",
"dataset:covid_qa_deepset",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | armageddon | null | armageddon/albert-squad-v2-covid-qa-deepset | 40 | null | transformers | 6,463 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- covid_qa_deepset
model-index:
- name: covid_qa_analysis_albert_base_squad_v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, ... |
QuickRead/pegasus-reddit-7e05 | f143e174018b5deaa9f5f89c1bc216fb12707a3c | 2022-03-15T17:13:28.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | QuickRead | null | QuickRead/pegasus-reddit-7e05 | 40 | null | transformers | 6,464 | Entry not found |
MarioBlue/Portuguese-Poems-Small-Gpt2 | 127c492b61ea4d86684842588e28fea1cd576cd6 | 2022-07-29T01:59:06.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | MarioBlue | null | MarioBlue/Portuguese-Poems-Small-Gpt2 | 40 | null | transformers | 6,465 | This is A GPT2 Fine Tuned Model for Poems in Portuguese
This Model is still not working properly,to generate a Poem you need to write on generator "Poema: [Tittle] \n" or just "Poema:" if you want the model to generate a tittle.
You are only allowed to use this software for academic purpose any commercial is not allow... |
alichte/TG-Relation-Model | 44133dec4604b0c375eb13b6fb54834aa2e941c2 | 2022-04-02T19:47:55.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | token-classification | false | alichte | null | alichte/TG-Relation-Model | 40 | null | transformers | 6,466 | ---
license: afl-3.0
---
|
alexjercan/codebert-base-buggy-token-classification | 72e54a618c91e21e8a89272d33f9d370e12bf4a4 | 2022-04-09T16:00:35.000Z | [
"pytorch",
"roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | alexjercan | null | alexjercan/codebert-base-buggy-token-classification | 40 | 1 | transformers | 6,467 | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: codebert-base-buggy-token-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, t... |
medhabi/distilbert-base-uncased-mlm-ta-local | 4ca17169c1392c6d114e2255aec2bd38c57e0cf5 | 2022-04-05T14:05:55.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | fill-mask | false | medhabi | null | medhabi/distilbert-base-uncased-mlm-ta-local | 40 | null | transformers | 6,468 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-mlm-ta-local
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. -->
... |
PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist | a3c852d467c4900d277dfe918a545346a5c736b4 | 2022-07-07T15:23:09.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:PlanTL-GOB-ES/cantemist-ner",
"arxiv:1907.11692",
"transformers",
"biomedical",
"clinical",
"eHR",
"spanish",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist | 40 | 1 | transformers | 6,469 | ---
language:
- es
tags:
- biomedical
- clinical
- eHR
- spanish
license: apache-2.0
datasets:
- "PlanTL-GOB-ES/cantemist-ner"
metrics:
- f1
model-index:
- name: PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist
results:
- task:
type: token-classification
dataset:
name: cantemist-ner
type: PlanTL-GOB... |
akoksal/bounti | ecfc692450eb64d2bbd3950e0c5e7ada89232de6 | 2022-04-11T20:12:25.000Z | [
"pytorch",
"bert",
"text-classification",
"tr",
"transformers",
"sentiment",
"twitter",
"turkish"
] | text-classification | false | akoksal | null | akoksal/bounti | 40 | null | transformers | 6,470 | ---
language: "tr"
tags:
- sentiment
- twitter
- turkish
---
This Turkish Sentiment Analysis model is a fine-tuned checkpoint of pretrained [BERTurk model 128k uncased](https://huggingface.co/dbmdz/bert-base-turkish-128k-uncased) with [BounTi dataset](https://ieeexplore.ieee.org/document/9477814).
## Usage in Hugging ... |
ken11/albert-base-japanese-v1-with-japanese-tokenizer | e1d6e479f98299eeab8ee82bf1288f862731e0e5 | 2022-04-20T17:28:13.000Z | [
"pytorch",
"tf",
"albert",
"fill-mask",
"ja",
"transformers",
"japanese",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | ken11 | null | ken11/albert-base-japanese-v1-with-japanese-tokenizer | 40 | null | transformers | 6,471 | ---
tags:
- fill-mask
- japanese
- albert
language:
- ja
license: mit
widget:
- text: "明日は明日の[MASK]が吹く"
---
## albert-base-japanese-v1-with-japanese
日本語事前学習済みALBERTモデルです
このモデルではTokenizerに[BertJapaneseTokenizerクラス](https://huggingface.co/docs/transformers/main/en/model_doc/bert-japanese#transformers.BertJapaneseTo... |
doc2query/msmarco-italian-mt5-base-v1 | 1fc4f8c520029aa0a92060c8b9ed632bf8b0568c | 2022-04-29T12:06:16.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"it",
"dataset:unicamp-dl/mmarco",
"arxiv:1904.08375",
"arxiv:2104.08663",
"arxiv:2112.07577",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | doc2query | null | doc2query/msmarco-italian-mt5-base-v1 | 40 | 1 | transformers | 6,472 | ---
language: it
datasets:
- unicamp-dl/mmarco
widget:
- text: "Python è un linguaggio di programmazione di alto livello, orientato a oggetti, adatto, tra gli altri usi, a sviluppare applicazioni distribuite, scripting, computazione numerica e system testing."
license: apache-2.0
---
# doc2query/msmarco-ita... |
allenai/ivila-block-layoutlm-finetuned-s2vl-v2 | af5f5335af8513f076460128208fd6a94d8fe5b1 | 2022-04-29T22:47:15.000Z | [
"pytorch",
"layoutlm",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | allenai | null | allenai/ivila-block-layoutlm-finetuned-s2vl-v2 | 40 | null | transformers | 6,473 | Entry not found |
TweebankNLP/bertweet-tb2_wnut17-ner | af754e27765c8c9db1ff7a31505a465000346aec | 2022-05-05T00:23:17.000Z | [
"pytorch",
"roberta",
"token-classification",
"arxiv:2201.07281",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | token-classification | false | TweebankNLP | null | TweebankNLP/bertweet-tb2_wnut17-ner | 40 | 1 | transformers | 6,474 | ---
license: cc-by-nc-4.0
---
## Model Specification
- This is the **state-of-the-art Twitter NER model (with 74.35\% Entity-Level F1)** on Tweebank V2's NER benchmark (also called `Tweebank-NER`), trained on the corpus combining both Tweebank-NER and WNUT 17 training data.
- For more details about the `TweebankNLP` p... |
sonoisa/sentence-bert-base-ja-en-mean-tokens | 51931e799ed487cedf94e7d6e382e06a9e196dbf | 2022-05-08T03:29:28.000Z | [
"pytorch",
"bert",
"feature-extraction",
"ja",
"sentence-transformers",
"sentence-bert",
"sentence-similarity",
"license:cc-by-sa-4.0"
] | feature-extraction | false | sonoisa | null | sonoisa/sentence-bert-base-ja-en-mean-tokens | 40 | 1 | sentence-transformers | 6,475 | ---
language: ja
license: cc-by-sa-4.0
tags:
- sentence-transformers
- sentence-bert
- feature-extraction
- sentence-similarity
---
This is a Japanese+English sentence-BERT model.
日本語+英語用Sentence-BERTモデルです。
[日本語のみバージョン](https://huggingface.co/sonoisa/sentence-bert-base-ja-mean-tokens-v2)と比べて、手元の非公開データセットでは日本語の精度が0.8p... |
deepgai/tweet_eval-sentiment-finetuned | aa1eb67695dbf99de9c720ddf505ee94d0400b6c | 2022-05-09T10:46:47.000Z | [
"pytorch",
"tensorboard",
"deberta-v2",
"text-classification",
"dataset:tweet_eval",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | deepgai | null | deepgai/tweet_eval-sentiment-finetuned | 40 | null | transformers | 6,476 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: tweet_eval-sentiment-finetuned
results:
- task:
name: Sentiment Analysis
type: sentiment-analysis
dataset:
name: tweeteval
type: tweeteval
args: default
metrics... |
emre/turkish-sentiment-analysis | 86f31923fda4bcec1c59218c4f0a4aa4938dc716 | 2022-05-15T22:07:26.000Z | [
"pytorch",
"bert",
"text-classification",
"tr",
"dataset:emre/autotrain-data-turkish-sentiment-analysis",
"transformers",
"autotrain",
"co2_eq_emissions"
] | text-classification | false | emre | null | emre/turkish-sentiment-analysis | 40 | null | transformers | 6,477 | ---
tags: autotrain
language: tr
widget:
- text: "Bu ürün gerçekten güzel çıktı"
datasets:
- emre/autotrain-data-turkish-sentiment-analysis
co2_eq_emissions: 120.82460124309924
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 870727732
- CO2 Emissions (in grams): 120.82460124... |
Remicm/sentiment-analysis-model-for-socialmedia | d6837382b32a7bffbde9d6fd7283c6f64933d86f | 2022-05-19T22:46:09.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | Remicm | null | Remicm/sentiment-analysis-model-for-socialmedia | 40 | null | transformers | 6,478 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: sentiment-analysis-model-for-socialmedia
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
me... |
nowalab/nepali-bert-npvec1 | a352715b9ba188fde67064a712cd82c40b8a4460 | 2022-05-25T05:58:47.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | nowalab | null | nowalab/nepali-bert-npvec1 | 40 | 1 | transformers | 6,479 | ---
license: apache-2.0
---
We are releasing the first BERT model trained on monolingual text for Nepali. Please refer our paper [NPVec1: Word Embeddings for Nepali - Construction and Evaluation](https://aclanthology.org/2021.repl4nlp-1.18.pdf) to get details on its construction and evaluation. |
Cristian-dcg/beto-sentiment-analysis-finetuned-onpremise | 562a37ff6841952b984ccbf22398e6152a5972a0 | 2022-06-07T22:36:41.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | Cristian-dcg | null | Cristian-dcg/beto-sentiment-analysis-finetuned-onpremise | 40 | null | transformers | 6,480 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beto-sentiment-analysis-finetuned-onpremise
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... |
RUCAIBox/mvp-story | c671474956d9a93fe68901fb4d40ef29e8ccd50d | 2022-06-27T02:28:15.000Z | [
"pytorch",
"mvp",
"en",
"arxiv:2206.12131",
"transformers",
"text-generation",
"text2text-generation",
"license:apache-2.0"
] | text2text-generation | false | RUCAIBox | null | RUCAIBox/mvp-story | 40 | null | transformers | 6,481 | ---
license: apache-2.0
language:
- en
tags:
- text-generation
- text2text-generation
pipeline_tag: text2text-generation
widget:
- text: "Given the story title: I think all public schools should have a uniform dress code."
example_title: "Example1"
- text: "Given the story title: My girlfriend and I decided to move t... |
rsuwaileh/IDRISI-LMR-HD-TL | 340690c67df4b45e6b5494cf591a71328d0a9ebd | 2022-07-18T09:16:29.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | rsuwaileh | null | rsuwaileh/IDRISI-LMR-HD-TL | 40 | null | transformers | 6,482 | This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/).
The model is trained using Hurricane Dorian 2019 event (training, development, and test data are used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRIS... |
wwbproj/empathic_conversations_dialog_acts | b6404104cc5dd3c98df42566f004332762958fcc | 2022-06-22T19:39:49.000Z | [
"pytorch",
"roberta",
"en",
"transformers"
] | null | false | wwbproj | null | wwbproj/empathic_conversations_dialog_acts | 40 | null | transformers | 6,483 | ---
language:
- en
---
# Empathic Conversations: Dialog Acts
Model owner(s): Ryan Guan, [rguan@seas.upenn.edu](mailto:rguan@seas.upenn.edu)
Associated paper:
## Model description
### Related models
- wwbproj/empathic_conversations_empathy
- wwbproj/empathic_conversations_emotion
- wwbproj/empathic_conversations_emo... |
robinhad/gpt2-uk-conversational | c70fdb543d8bf0509e5787ce3a7e768ef52e6991 | 2022-06-14T20:02:33.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"license:mit"
] | conversational | false | robinhad | null | robinhad/gpt2-uk-conversational | 40 | 3 | transformers | 6,484 | ---
tags:
- conversational
license: mit
widget:
- text: "привіт, як тебе звати?"
example_title: "Питаємо ім'я"
---
# Ukrainian AI chatbot alpha release
This model was trained on dataset of movie dialogs (uncleaned) from opensubtitles.org.
Link to training scripts: [https://github.com/robinhad/ukrainian-ai](https:/... |
huggingtweets/unknownco123 | 2308321bddeab6c1eb7b8e8129362782f3f676d2 | 2022-06-16T16:20:12.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/unknownco123 | 40 | null | transformers | 6,485 | ---
language: en
thumbnail: http://www.huggingtweets.com/unknownco123/1655396407192/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; wi... |
bookpanda/wangchanberta-base-att-spm-uncased-masking | d124223e6c095758652a21a2721540ac0818d423 | 2022-06-19T11:05:59.000Z | [
"pytorch",
"camembert",
"fill-mask",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | bookpanda | null | bookpanda/wangchanberta-base-att-spm-uncased-masking | 40 | null | transformers | 6,486 | ---
tags:
- generated_from_trainer
model-index:
- name: wangchanberta-base-att-spm-uncased-masking
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. -->
# wangchanbert... |
Lexemo/roberta_large_legal_act_extraction | e29807386021b28c685254bcfcc4ebd74edd3af0 | 2022-06-24T12:03:38.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"transformers",
"license:mit",
"autotrain_compatible"
] | token-classification | false | Lexemo | null | Lexemo/roberta_large_legal_act_extraction | 40 | null | transformers | 6,487 | ---
language: en
license: mit
metrics:
- seqeval
widget:
- text: "When Member States adopt those measures, they shall contain a reference to this Directive or be accompanied by such reference on the occasion of their official publication. They shall also include a statement that references in existing laws, regulations... |
Aalaa/opt-125m-finetuned-wikitext2 | b12ee7517bedff672d31715d19ac60cc1563b6dd | 2022-06-28T03:30:55.000Z | [
"pytorch",
"tensorboard",
"opt",
"text-generation",
"transformers",
"generated_from_trainer",
"license:other",
"model-index"
] | text-generation | false | Aalaa | null | Aalaa/opt-125m-finetuned-wikitext2 | 40 | null | transformers | 6,488 | ---
license: other
tags:
- generated_from_trainer
model-index:
- name: opt-125m-finetuned-wikitext2
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. -->
# opt-125m-fi... |
cambridgeltl/mle_cnwikitext | 011a9386596ff03303ca005940fcbdfc4702fb68 | 2022-07-03T20:48:42.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | cambridgeltl | null | cambridgeltl/mle_cnwikitext | 40 | null | transformers | 6,489 | Entry not found |
zhifei/autotrain-chineses-title-summarization-3-1087939403 | cad095fa0b7da79b48f5a1ec5ae6ef5665082680 | 2022-07-05T02:45:16.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"unk",
"dataset:zhifei/autotrain-data-chineses-title-summarization-3",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | zhifei | null | zhifei/autotrain-chineses-title-summarization-3-1087939403 | 40 | null | transformers | 6,490 | ---
tags: autotrain
language: unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- zhifei/autotrain-data-chineses-title-summarization-3
co2_eq_emissions: 0.004900087842646563
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1087939403
- CO2 Emissions (in grams): 0.004900087842646563
## ... |
danieleV9H/wavlm-base-plus-ft-cv3 | 33063d64180702c07f00c8bfcaa81afe48f0fdd5 | 2022-07-23T15:42:47.000Z | [
"pytorch",
"tensorboard",
"wavlm",
"automatic-speech-recognition",
"en",
"dataset:mozilla-foundation/common_voice_3_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model-index"
] | automatic-speech-recognition | false | danieleV9H | null | danieleV9H/wavlm-base-plus-ft-cv3 | 40 | null | transformers | 6,491 | ---
tags:
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_3_0
model-index:
- name: wavlm-base-plus-ft-cv3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: LibriSpeech (clean)
type: librispeech_... |
Aktsvigun/bart-base_aeslc_42 | 8e472a9b1ed30a899ac2fa051a9423e039d238dd | 2022-07-07T15:44:24.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Aktsvigun | null | Aktsvigun/bart-base_aeslc_42 | 40 | null | transformers | 6,492 | Entry not found |
BigSalmon/GPTNeo1.3BInformalToFormal | 1f64abdeba88796c6268597ef6e37eeeb676a2e9 | 2022-07-17T14:11:25.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | BigSalmon | null | BigSalmon/GPTNeo1.3BInformalToFormal | 40 | null | transformers | 6,493 | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/GPTNeo1.3BInformalToFormal")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/GPTNeo1.3BInformalToForma")
```
```
How To Make Prompt:
informal english: i am very ready to do that just that.
Tr... |
Ahmed007/T5-as-chat-bot | f4824f01599970a8a94bceeedb62b7f776588b6c | 2022-07-19T20:20:47.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | Ahmed007 | null | Ahmed007/T5-as-chat-bot | 40 | null | transformers | 6,494 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: T5-as-chat-bot
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. -->
# T5-as-chat-bot
This... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth | 3b9835199ee8e65c65ca320567fe8e5a5ca3698c | 2021-09-14T14:26:07.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth | 39 | 2 | transformers | 6,495 | ---
language:
- ar
license: apache-2.0
widget:
- text: "الهدف من الحياة هو [MASK] ."
---
# CAMeLBERT: A collection of pre-trained models for Arabic NLP tasks
## Model description
**CAMeLBERT** is a collection of BERT models pre-trained on Arabic texts with different sizes and variants.
We release pre-trained langu... |
Emanuel/autonlp-pos-tag-bosque | 145a83cb3b508cd334eae8dcfa370ed653a9308d | 2021-10-19T12:09:29.000Z | [
"pytorch",
"bert",
"token-classification",
"pt",
"dataset:Emanuel/autonlp-data-pos-tag-bosque",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | token-classification | false | Emanuel | null | Emanuel/autonlp-pos-tag-bosque | 39 | 2 | transformers | 6,496 | ---
tags: autonlp
language: pt
widget:
- text: "I love AutoNLP 🤗"
datasets:
- Emanuel/autonlp-data-pos-tag-bosque
co2_eq_emissions: 6.2107269129101805
---
# Model Trained Using AutoNLP
- Problem type: Entity Extraction
- Model ID: 21124427
- CO2 Emissions (in grams): 6.2107269129101805
## Validation Metrics
- Loss... |
Geotrend/bert-base-pt-cased | 793cd00d9242c56f3dccf438a75966f92035b487 | 2021-05-18T20:06:41.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"pt",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-pt-cased | 39 | null | transformers | 6,497 | ---
language: pt
datasets: wikipedia
license: apache-2.0
---
# bert-base-pt-cased
We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) that handle a custom number of languages.
Unlike [distilbert-base-multilingual-cased](https://huggingface.co/disti... |
HScomcom/gpt2-fairytales | 8c9263255ae9c24840546543defd0cbf072f38a0 | 2021-05-21T10:16:43.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | HScomcom | null | HScomcom/gpt2-fairytales | 39 | null | transformers | 6,498 | ### Model information
Fine tuning data: https://www.kaggle.com/cuddlefish/fairy-tales
License: CC0: Public Domain
Base model: gpt-2 large
Epoch: 30
Train runtime: 17861.6048 secs
Loss: 0.0412
API page: [Ainize](https://ainize.ai/fpem123/GPT2-FairyTales?branch=master)
Demo page: [End-... |
Hate-speech-CNERG/dehatebert-mono-polish | ec586b2e2e6140879c6f533ccd5208d1c2692715 | 2021-09-25T13:58:40.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"pl",
"arxiv:2004.06465",
"transformers",
"license:apache-2.0"
] | text-classification | false | Hate-speech-CNERG | null | Hate-speech-CNERG/dehatebert-mono-polish | 39 | null | transformers | 6,499 | ---
language: pl
license: apache-2.0
---
This model is used detecting **hatespeech** in **Polish language**. The mono in the name refers to the monolingual setting, where the model is trained using only English language data. It is finetuned on multilingual bert model.
The model is trained with different learning rates... |
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