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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
BSC-TeMU/roberta-large-bne-capitel-pos | 6ddd4a469f2a48870891d043ed34abe962a9f16a | 2021-10-21T10:31:47.000Z | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"pos",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | BSC-TeMU | null | BSC-TeMU/roberta-large-bne-capitel-pos | 26 | 3 | transformers | 7,500 | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "capitel"
- "pos"
datasets:
- "bne"
- "capitel"
metrics:
- "f1"
widget:
- text: "Festival de San Sebastián: Johnny Depp recibirá el premio Donostia en pleno rifirrafe judicial con Amber Heard"
- text: "El alcalde de Vigo... |
BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | 933447601c98ddcc59e5a79fe03d2a8d0e124d89 | 2022-02-03T15:17:21.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:squad",
"arxiv:1910.01108",
"transformers",
"question-answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | BatuhanYilmaz | null | BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | 26 | null | transformers | 7,501 | ---
language:
- en
thumbnail: https://github.com/karanchahal/distiller/blob/master/distiller.jpg
tags:
- question-answering
license: apache-2.0
datasets:
- squad
metrics:
- squad
---
# DistilBERT with a second step of distillation
## Model description
This model replicates the "DistilBERT (D)" model from Table 2 of... |
CAMeL-Lab/bert-base-arabic-camelbert-da-ner | 36e7d767d339b7ed97e8861245db2aef8cb4aa03 | 2021-10-17T11:13:27.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-da-ner | 26 | null | transformers | 7,502 | ---
language:
- ar
license: apache-2.0
widget:
- text: "إمارة أبوظبي هي إحدى إمارات دولة الإمارات العربية المتحدة السبع"
---
# CAMeLBERT-DA NER Model
## Model description
**CAMeLBERT-DA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://hu... |
Cameron/BERT-mdgender-convai-binary | beb052a4dc3e234ff1dc25d3e28820d69532d722 | 2021-05-18T17:30:21.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Cameron | null | Cameron/BERT-mdgender-convai-binary | 26 | null | transformers | 7,503 | Entry not found |
CouchCat/ma_sa_v7_distil | 43770a92bed3d5bb5a8da1472eadb83dfd365006 | 2021-02-15T23:19:57.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"sentiment-analysis",
"license:mit"
] | text-classification | false | CouchCat | null | CouchCat/ma_sa_v7_distil | 26 | null | transformers | 7,504 | ---
language: en
license: mit
tags:
- sentiment-analysis
widget:
- text: "I am disappointed in the terrible quality of my dress"
---
### Description
A Sentiment Analysis model trained on customer feedback data using DistilBert.
Possible sentiments are:
* negative
* neutral
* positive
### Usage
```
from transformers ... |
Davlan/xlm-roberta-large-masakhaner | 36e6b01b4ebd3afc282e0ce198d0a04ddbfd58a8 | 2022-06-27T11:50:50.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"amh",
"hau",
"ibo",
"kin",
"lug",
"luo",
"pcm",
"swa",
"wol",
"yor",
"multilingual",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | false | Davlan | null | Davlan/xlm-roberta-large-masakhaner | 26 | null | transformers | 7,505 | Hugging Face's logo
---
language:
- amh
- hau
- ibo
- kin
- lug
- luo
- pcm
- swa
- wol
- yor
- multilingual
datasets:
- masakhaner
---
# xlm-roberta-large-masakhaner
## Model description
**xlm-roberta-large-masakhaner** is the first **Named Entity Recognition** model for 10 African languages (Amharic, Hausa, Igbo, ... |
DrMatters/rubert_cased | 58badf1655b5856f08b90eb14313fa4a3405ece9 | 2021-05-19T11:14:32.000Z | [
"pytorch",
"jax",
"bert",
"transformers"
] | null | false | DrMatters | null | DrMatters/rubert_cased | 26 | null | transformers | 7,506 | Entry not found |
EleutherAI/enformer-191k_corr_coef_obj | 5c9d4159c1815c487b206367493033d113fa3eea | 2022-02-23T12:17:55.000Z | [
"pytorch",
"enformer",
"transformers",
"license:apache-2.0"
] | null | false | EleutherAI | null | EleutherAI/enformer-191k_corr_coef_obj | 26 | null | transformers | 7,507 | ---
license: apache-2.0
inference: false
---
# Enformer
Enformer model. It was introduced in the paper [Effective gene expression prediction from sequence by integrating long-range interactions.](https://www.nature.com/articles/s41592-021-01252-x) by Avsec et al. and first released in [this repository](https://github... |
Elron/bleurt-base-128 | 3dabe1a4ba7ca2041f5455262780ab797f0f7d0b | 2021-10-04T13:24:42.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | Elron | null | Elron/bleurt-base-128 | 26 | 1 | transformers | 7,508 | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... |
HJK/PickupLineGenerator | 9f62120ac2b28ef67731c4e5d41073d09a02b560 | 2021-05-21T10:05:21.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | HJK | null | HJK/PickupLineGenerator | 26 | null | transformers | 7,509 | basically, it makes pickup lines
https://huggingface.co/gpt2
|
Helsinki-NLP/opus-mt-bem-en | 8175ad6e29c44d6aa61a3cc3e0cc6b89432be48e | 2021-09-09T21:27:03.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bem",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-bem-en | 26 | null | transformers | 7,510 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-bem-en
* source languages: bem
* target languages: en
* OPUS readme: [bem-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bem-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-en-niu | f52877dc5488bf560017c19e65a545112d7a8ec8 | 2021-09-09T21:38:01.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"niu",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-en-niu | 26 | null | transformers | 7,511 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-en-niu
* source languages: en
* target languages: niu
* OPUS readme: [en-niu](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-niu/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... |
Helsinki-NLP/opus-mt-es-hr | 27f3c1660c42cb2fc6267a557debf6cfbeaae583 | 2021-09-09T21:42:54.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"hr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-hr | 26 | null | transformers | 7,512 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-es-hr
* source languages: es
* target languages: hr
* OPUS readme: [es-hr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-hr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ine-ine | 82a5f65abdd0e196b05112464ff3dd552d484283 | 2020-08-21T14:42:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ca",
"es",
"os",
"ro",
"fy",
"cy",
"sc",
"is",
"yi",
"lb",
"an",
"sq",
"fr",
"ht",
"rm",
"ps",
"af",
"uk",
"sl",
"lt",
"bg",
"be",
"gd",
"si",
"en",
"br",
"mk",
"or",
"mr",
"ru",
"fo",
"co",
"oc",
"... | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ine-ine | 26 | null | transformers | 7,513 | ---
language:
- ca
- es
- os
- ro
- fy
- cy
- sc
- is
- yi
- lb
- an
- sq
- fr
- ht
- rm
- ps
- af
- uk
- sl
- lt
- bg
- be
- gd
- si
- en
- br
- mk
- or
- mr
- ru
- fo
- co
- oc
- pl
- gl
- nb
- bn
- id
- hy
- da
- gv
- nl
- pt
- hi
- as
- kw
- ga
- sv
- gu
- wa
- lv
- el
- it
- hr
- ur
- nn
- de
- cs
- ine
tags:
- ... |
Helsinki-NLP/opus-mt-mkh-en | 325cb2363f097b102d7599b518ba64d8bf98de3a | 2020-08-21T14:42:48.000Z | [
"pytorch",
"marian",
"text2text-generation",
"vi",
"km",
"mkh",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-mkh-en | 26 | null | transformers | 7,514 | ---
language:
- vi
- km
- mkh
- en
tags:
- translation
license: apache-2.0
---
### mkh-eng
* source group: Mon-Khmer languages
* target group: English
* OPUS readme: [mkh-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/mkh-eng/README.md)
* model: transformer
* source language(s): kha... |
Helsinki-NLP/opus-mt-nl-fi | 9c2749217bb778e6d77a7bffba719d98a27c7f10 | 2021-09-10T13:59:15.000Z | [
"pytorch",
"marian",
"text2text-generation",
"nl",
"fi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-nl-fi | 26 | null | transformers | 7,515 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-nl-fi
* source languages: nl
* target languages: fi
* OPUS readme: [nl-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/nl-fi/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-sn-en | 122bc773e49e14db353cea778090a95ce2e20f6c | 2021-09-10T14:04:04.000Z | [
"pytorch",
"marian",
"text2text-generation",
"sn",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-sn-en | 26 | null | transformers | 7,516 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-sn-en
* source languages: sn
* target languages: en
* OPUS readme: [sn-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/sn-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-xh-en | 6a5f51b69435fc8f618c0b9c1711d6dd322c5661 | 2021-09-11T10:52:20.000Z | [
"pytorch",
"marian",
"text2text-generation",
"xh",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-xh-en | 26 | null | transformers | 7,517 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-xh-en
* source languages: xh
* target languages: en
* OPUS readme: [xh-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/xh-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-tatoeba-fr-it | ece0ee5246a0e21bba190007872250a79cc262bd | 2021-11-11T17:41:18.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fr",
"it",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-tatoeba-fr-it | 26 | null | transformers | 7,518 | ---
language:
- fr
- it
tags:
- translation
license: apache-2.0
---
### fr-it
* source group: French
* target group: Italian
* OPUS readme: [fra-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-ita/README.md)
* model: transformer-align
* source language(s): fra
* target language(s):... |
KoichiYasuoka/bert-large-japanese-upos | 45d90ca233f9496c9aacfaa6407e510fb7901122 | 2022-05-23T21:51:21.000Z | [
"pytorch",
"bert",
"token-classification",
"ja",
"dataset:universal_dependencies",
"transformers",
"japanese",
"pos",
"wikipedia",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/bert-large-japanese-upos | 26 | 1 | transformers | 7,519 | ---
language:
- "ja"
tags:
- "japanese"
- "token-classification"
- "pos"
- "wikipedia"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "国境の長いトンネルを抜けると雪国であった。"
---
# bert-large-japanese-upos
## Model Description
This is a BERT mo... |
Kowsher/bert-base-bangla-ner | 185e29349c9687fa704c12f8d9a5dd494a422b08 | 2021-08-08T10:35:26.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Kowsher | null | Kowsher/bert-base-bangla-ner | 26 | null | transformers | 7,520 | Entry not found |
NLPC-UOM/SinBERT-small | f0eaaed69eaba28a4f98eaa31b92713c5c01e1db | 2022-04-29T05:04:13.000Z | [
"pytorch",
"roberta",
"fill-mask",
"si",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | NLPC-UOM | null | NLPC-UOM/SinBERT-small | 26 | 1 | transformers | 7,521 | ---
license: mit
language:
- si
---
This is SinBERT-small model. SinBERT models are pretrained on a large Sinhala monolingual corpus (sin-cc-15M) using RoBERTa. If you use this model, please cite *BERTifying Sinhala - A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classification, LREC 2022*
|
NYTK/text-generation-poem-petofi-gpt2-small-hungarian | d338bd8974e927955d676045a95980cde2d21d66 | 2022-02-14T13:34:21.000Z | [
"pytorch",
"gpt2",
"text-generation",
"hu",
"transformers",
"license:gpl"
] | text-generation | false | NYTK | null | NYTK/text-generation-poem-petofi-gpt2-small-hungarian | 26 | 1 | transformers | 7,522 | ---
language:
- hu
tags:
- text-generation
license: gpl
widget:
- text: "Szegeden, január végén,"
---
# Hungarian GPT-2 poem generator in Petőfi style
For further models, scripts and details, see [our repository](https://github.com/nytud/neural-models) or [our demo site](https://juniper.nytud.hu/demo/nlp).
- Pre... |
SEBIS/code_trans_t5_small_commit_generation_multitask_finetune | ccb87cb56e45b0e940a1753c219bc82d1e3dd320 | 2021-06-23T10:15:17.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_small_commit_generation_multitask_finetune | 26 | null | transformers | 7,523 | ---
tags:
- summarization
widget:
- text: "new file mode 100644 index 000000000 . . 892fda21b Binary files / dev / null and b / src / plugins / gateway / lib / joscar . jar differ"
---
# CodeTrans model for git commit message generation
Pretrained model on git commit using the t5 small model architecture. It was fir... |
SEBIS/legal_t5_small_trans_en_sv_small_finetuned | 59e08a5da640a659ab998f79b390e2289602c01b | 2021-06-23T09:40:43.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"English Swedish",
"dataset:dcep europarl jrc-acquis",
"transformers",
"translation English Swedish model",
"autotrain_compatible"
] | text2text-generation | false | SEBIS | null | SEBIS/legal_t5_small_trans_en_sv_small_finetuned | 26 | null | transformers | 7,524 |
---
language: English Swedish
tags:
- translation English Swedish model
datasets:
- dcep europarl jrc-acquis
widget:
- text: "any operations cofinanced in the framework of"
---
# legal_t5_small_trans_en_sv_small_finetuned model
Model on translating legal text from English to Swedish. It was first released in
[th... |
ShengdingHu/sst2 | 894b64b74eab3740d4e91840a826f939c2e6baf7 | 2022-04-26T11:16:23.000Z | [
"pytorch",
"tensorboard",
"big_bird",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | ShengdingHu | null | ShengdingHu/sst2 | 26 | null | transformers | 7,525 | Entry not found |
addy88/programming-lang-identifier | 8b13668b138d4dbd1cce7d5febc4261bcdd7cf24 | 2022-01-04T04:22:07.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | addy88 | null | addy88/programming-lang-identifier | 26 | null | transformers | 7,526 | This model is funetune version of Codebert in roberta. On CodeSearchNet.
###
Quick start:
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("addy88/programming-lang-identifier")
model = AutoModelForSequenceClassification.from_pretrained("addy88/progr... |
akdeniz27/mDeBERTa-v3-base-turkish-ner | 0548ce8e7f7ddcc165e12cd9cfcac01a6490fbbf | 2021-11-25T20:32:19.000Z | [
"pytorch",
"deberta-v2",
"token-classification",
"tr",
"transformers",
"autotrain_compatible"
] | token-classification | false | akdeniz27 | null | akdeniz27/mDeBERTa-v3-base-turkish-ner | 26 | null | transformers | 7,527 | ---
language: tr
widget:
- text: "Mustafa Kemal Atatürk 19 Mayıs 1919'da Samsun'a çıktı."
---
# Turkish Named Entity Recognition (NER) Model
This model is the fine-tuned version of "microsoft/mDeBERTa-v3-base"
(a multilingual version of DeBERTa V3)
using a reviewed version of well known Turkish NER dataset
(https://g... |
allenai/hvila-block-layoutlm-finetuned-grotoap2 | c2c2e944ea28883b5a8184d76354e53c6064b83d | 2021-09-27T22:59:48.000Z | [
"pytorch",
"hierarchical_model",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | allenai | null | allenai/hvila-block-layoutlm-finetuned-grotoap2 | 26 | null | transformers | 7,528 | Entry not found |
anuragshas/wav2vec2-large-xlsr-as | d69474818224e8ecf85d09954eb0079467587ad0 | 2022-01-14T16:41:25.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"as",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anuragshas | null | anuragshas/wav2vec2-large-xlsr-as | 26 | null | transformers | 7,529 | ---
language: as
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Anurag Singh XLSR Wav2Vec2 Large 53 Assamese
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
arjuntheprogrammer/distilbert-base-multilingual-cased-sentiment-2 | fc07afdd922e42e34c67464e895d5a0e4f2565e8 | 2022-02-02T15:16:39.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:amazon_reviews_multi",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | arjuntheprogrammer | null | arjuntheprogrammer/distilbert-base-multilingual-cased-sentiment-2 | 26 | null | transformers | 7,530 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-multilingual-cased-sentiment-2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
ty... |
ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa | ff8dd3f1de9be2cd3cf57783ae27f9972a55ede8 | 2021-12-22T10:33:50.000Z | [
"pytorch",
"roberta",
"text-classification",
"dataset:indonlu",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-classification | false | ayameRushia | null | ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa | 26 | null | transformers | 7,531 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
model-index:
- name: roberta-base-indonesian-sentiment-analysis-smsa
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: indonlu
type: indonlu
args: smsa
metr... |
bakrianoo/t5-arabic-large | f60d15333498962977d518ec27331d35bc17fdbf | 2021-06-26T17:09:24.000Z | [
"pytorch",
"t5",
"text2text-generation",
"Arabic",
"dataset:mc4",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | bakrianoo | null | bakrianoo/t5-arabic-large | 26 | null | transformers | 7,532 | ---
language: Arabic
datasets:
- mc4
license: apache-2.0
---
## Arabic T5 Large Model
A customized T5 Model for Arabic and English Task. It could be used as an alternative for `google/mt5-large` model, as it's much smaller and only targets Arabic and English based tasks.
### About T5
```
T5 is an encoder-decoder mo... |
bipin/malayalam-news-classifier | b14c5e159c1811bcaec8bd213142493252cc4f94 | 2021-07-21T13:40:25.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"malayalam",
"license:mit"
] | text-classification | false | bipin | null | bipin/malayalam-news-classifier | 26 | 2 | transformers | 7,533 | ---
license: mit
tags:
- text-classification
- roberta
- malayalam
- pytorch
widget:
- text: "2032 ഒളിമ്പിക്സിന് ബ്രിസ്ബെയ്ന് വേദിയാകും; ഗെയിംസിന് വേദിയാകുന്ന മൂന്നാമത്തെ ഓസ്ട്രേലിയന് നഗരം"
---
## Malayalam news classifier
### Overview
This model is trained on top of [MalayalamBert](https://huggingface.co/... |
cl-tohoku/roberta-base-japanese | 626ec58f01e6aa050dde737d1e5f41654c89e489 | 2021-09-21T09:31:46.000Z | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cl-tohoku | null | cl-tohoku/roberta-base-japanese | 26 | null | transformers | 7,534 | Entry not found |
codesj/empathic-concern | be3878da3f8bf9d739dc51d19e54cb360a8116d6 | 2021-11-15T15:10:47.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | codesj | null | codesj/empathic-concern | 26 | null | transformers | 7,535 | Entry not found |
daekeun-ml/koelectra-small-v3-nsmc | 7d03233da5e3fefe54ed4eb20d9d94d45d180fe1 | 2022-02-13T06:22:54.000Z | [
"pytorch",
"electra",
"text-classification",
"ko",
"dataset:nsmc",
"transformers",
"classification",
"license:mit"
] | text-classification | false | daekeun-ml | null | daekeun-ml/koelectra-small-v3-nsmc | 26 | null | transformers | 7,536 | ---
language:
- ko
tags:
- classification
license: mit
datasets:
- nsmc
metrics:
- accuracy
- f1
- precision
- recall- accuracy
---
# Sentiment Binary Classification (fine-tuning with KoELECTRA-Small-v3 model and Naver Sentiment Movie Corpus dataset)
## Usage (Amazon SageMaker inference applicable)
It uses the int... |
dbmdz/electra-base-turkish-cased-generator | d743f2f14112ced2d7ecd9cd3a6eb623b67be35c | 2020-05-12T11:54:58.000Z | [
"pytorch",
"tf",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/electra-base-turkish-cased-generator | 26 | null | transformers | 7,537 | Entry not found |
dropout05/t5-tiny | a078917e9be9c9c653ddc8397b5a61c1cc0a1012 | 2022-02-02T19:11:43.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | dropout05 | null | dropout05/t5-tiny | 26 | null | transformers | 7,538 | ---
license: apache-2.0
---
|
eunjin/kogpt2-finetuned-wellness | d8f79be7e2971828a2a269453927649c8ce0d6dd | 2021-06-10T12:32:15.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | eunjin | null | eunjin/kogpt2-finetuned-wellness | 26 | null | transformers | 7,539 | * skt/kogpt2-base-v2에 wellness 및 일상챗봇 데이터를 fine-tuning한 모델입니다.
* 유사한 정신건강 상담 도메인에서 바로 사용 가능합니다.
* 깃허브 사이트를 참조해주세요! https://github.com/eunjiinkim/WellnessChatbot |
ffsouza/tiny-mbart-length-128-learning_rate-2e-05-weight_decay-0.01-finetuned-en-to-ro | 050c773cc8312ff52f0780ed148623cc63d00c79 | 2021-11-30T16:02:14.000Z | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"dataset:wmt16_en_ro_pre_processed",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | ffsouza | null | ffsouza/tiny-mbart-length-128-learning_rate-2e-05-weight_decay-0.01-finetuned-en-to-ro | 26 | null | transformers | 7,540 | ---
tags:
- generated_from_trainer
datasets:
- wmt16_en_ro_pre_processed
metrics:
- bleu
model-index:
- name: tiny-mbart-length-128-learning_rate-2e-05-weight_decay-0.01-finetuned-en-to-ro
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: w... |
gfdgdfgdg/arap_qa_bert_large_v2 | ecda3a63abebf8bf9df8b8369037996bf910f8c9 | 2021-08-09T12:52:24.000Z | [
"pytorch",
"bert",
"question-answering",
"ar",
"transformers",
"autotrain_compatible"
] | question-answering | false | gfdgdfgdg | null | gfdgdfgdg/arap_qa_bert_large_v2 | 26 | null | transformers | 7,541 | ---
language:
- ar
widget:
- text: "أين يعيش محمد ؟"
context: "اسمي محمد وأنا أعيش في سوريا"
- text: "ما العدد الذري للهيدروجين ؟"
context: "الهيدروجين هو عنصر كيميائي عدده الذري 1 ، وهو غاز عديم الرائحة واللون وهو سريع الاشتعال"
- text: "ما خواص الهيدروجين ؟"
context: "الهيدروجين هو عنصر كيميائي عدده الذري 1 ، ... |
google/t5-11b-ssm-wq | 91862905ed9515c5e86f1d5dfcc2c529212ecdb5 | 2020-12-07T08:46:12.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"dataset:wikipedia",
"dataset:web_questions",
"arxiv:2002.08909",
"arxiv:1910.10683",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-11b-ssm-wq | 26 | 1 | transformers | 7,542 | ---
language: en
datasets:
- c4
- wikipedia
- web_questions
license: apache-2.0
---
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) for **Closed Book Question Answering**.
The model was pre-trained using T5's denoising objective on [C4](https://huggingface.co/datasets/c4), s... |
huggingtweets/14werewolfvevo | e109cae8b231744821655e7a2ea9adc36c2cdb52 | 2021-05-21T16:28:48.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/14werewolfvevo | 26 | null | transformers | 7,543 | ---
language: en
thumbnail: https://www.huggingtweets.com/14werewolfvevo/1617769919321/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/1343113335... |
huggingtweets/davidgoggins | 122f2d567287b77bfa57a6e29239934505404315 | 2021-05-22T00:53:20.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/davidgoggins | 26 | null | transformers | 7,544 | ---
language: en
thumbnail: https://www.huggingtweets.com/davidgoggins/1603830361250/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... |
huggingtweets/jschlatt | 878fb0fe0d8e787668214110f723d0c186fad9c3 | 2021-09-23T19:13:50.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/jschlatt | 26 | null | transformers | 7,545 | ---
language: en
thumbnail: https://www.huggingtweets.com/jschlatt/1632424426297/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width... |
huggingtweets/marsajal | 81cf502acb44411e859f7e6ef7da1775e4fc19df | 2022-07-07T09:42:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/marsajal | 26 | null | transformers | 7,546 | ---
language: en
thumbnail: http://www.huggingtweets.com/marsajal/1657186931820/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width:... |
huggingtweets/sexycuckolding | d31fe2d73e60b70cf63dd5326c88631aba96a6f4 | 2021-08-14T12:11:30.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/sexycuckolding | 26 | null | transformers | 7,547 | ---
language: en
thumbnail: https://www.huggingtweets.com/sexycuckolding/1628943086648/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;... |
huggingtweets/starbannergames | 9252d512ad61e38345affc7583503e0eb8fb6b4f | 2021-05-22T23:54:53.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/starbannergames | 26 | null | transformers | 7,548 | ---
language: en
thumbnail: https://www.huggingtweets.com/starbannergames/1616902434636/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/136466996... |
huggingtweets/ylecun | 3575ada0ee67c8e05347c9f043fe2fa99722d57b | 2021-05-23T05:03:08.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/ylecun | 26 | null | transformers | 7,549 | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
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) {
.pros... |
ishan/distilbert-base-uncased-mnli | 5b5436f6f59086b00ac829afecc16d1bd926cbfb | 2020-08-21T10:23:40.000Z | [
"pytorch",
"distilbert",
"text-classification",
"en",
"dataset:MNLI",
"arxiv:1810.04805",
"transformers"
] | text-classification | false | ishan | null | ishan/distilbert-base-uncased-mnli | 26 | null | transformers | 7,550 | ---
language: en
thumbnail:
tags:
- pytorch
- text-classification
datasets:
- MNLI
---
# distilbert-base-uncased finetuned on MNLI
## Model Details and Training Data
We used the pretrained model from [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) and finetuned it on [MultiNLI](https://cim... |
jaketae/hifigan-lj-v1 | 85caaf4ed15cfb83ba79a994a2266aa892645495 | 2022-02-23T23:22:01.000Z | [
"pytorch",
"hifigan",
"en",
"dataset:ljspeech",
"arxiv:2010.05646",
"transformers",
"audio",
"text-to-speech"
] | text-to-speech | false | jaketae | null | jaketae/hifigan-lj-v1 | 26 | null | transformers | 7,551 | ---
language: en
datasets:
- ljspeech
tags:
- audio
- text-to-speech
---
# HiFi-GAN
[HiFi-GAN](https://arxiv.org/abs/2010.05646) vocoder trained on the [LJ Speech dataset](https://keithito.com/LJ-Speech-Dataset/). The modeling code is based on the [official implementation](https://github.com/jik876/hifi-gan) and the ... |
justinqbui/bertweet-covid19-base-uncased-pretraining-covid-vaccine-tweets | 5d61a1b0771e7816cb449f526c93f554ba632926 | 2021-12-12T20:00:43.000Z | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"arxiv:1907.11692",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | justinqbui | null | justinqbui/bertweet-covid19-base-uncased-pretraining-covid-vaccine-tweets | 26 | null | transformers | 7,552 | ---
tags:
- generated_from_trainer
model-index:
- name: bertweet-covid19-base-uncased-pretraining-covid-vaccine-tweets
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.... |
kmfoda/wav2vec2-large-xlsr-arabic | cd5511440ff945978f812dc85c8c410e9ca12cdb | 2021-07-06T09:45:10.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | kmfoda | null | kmfoda/wav2vec2-large-xlsr-arabic | 26 | null | transformers | 7,553 | ---
language: ar
datasets:
- common_voice
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Arabic by Othmane Rifki
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset... |
kuppuluri/telugu_bertu_tydiqa | b67e93cd5ae0fb5165ca2ed88023cf66d898963f | 2021-12-02T18:15:25.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | kuppuluri | null | kuppuluri/telugu_bertu_tydiqa | 26 | null | transformers | 7,554 | # Telugu Question-Answering model trained on Tydiqa dataset from Google
#### How to use
Use the below script from your python terminal as the web interface for inference has few encoding issues for Telugu
```python
from transformers.pipelines import pipeline, AutoModelForQuestionAnswering, AutoTokenizer
model = AutoMo... |
maroo93/squad2.0 | 2f0cb49fb8a12dfa44fd52589874eaacb8a45dfd | 2021-05-19T23:09:45.000Z | [
"pytorch",
"jax",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | maroo93 | null | maroo93/squad2.0 | 26 | null | transformers | 7,555 | Entry not found |
mlcorelib/debertav2-base-uncased | 55519d4c151b1a15fd62273a084a7313a251e27e | 2021-05-01T12:53:51.000Z | [
"pytorch",
"tf",
"jax",
"rust",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | mlcorelib | null | mlcorelib/debertav2-base-uncased | 26 | null | transformers | 7,556 | ---
language: en
tags:
- exbert
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
---
# BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in
[this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](http... |
monologg/koelectra-v3-klue-sts | cf2810bfb9a91714e9c3b20dfa171ef9adf77770 | 2022-01-25T09:13:15.000Z | [
"pytorch",
"electra",
"text-classification",
"transformers"
] | text-classification | false | monologg | null | monologg/koelectra-v3-klue-sts | 26 | null | transformers | 7,557 | Entry not found |
mustapha/distilgpt2-finetuned-wikitext2 | 76f63a314a775840ffaaa10ee03e0e615a386388 | 2021-11-30T09:52:12.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-generation | false | mustapha | null | mustapha/distilgpt2-finetuned-wikitext2 | 26 | 1 | transformers | 7,558 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-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. -->
# dist... |
patrickvonplaten/sew-d-small-100k-timit | 3ba41fac89042fbac19b762eb3cbc42db3703e16 | 2021-10-27T17:15:26.000Z | [
"pytorch",
"tensorboard",
"sew-d",
"automatic-speech-recognition",
"dataset:timit_asr",
"transformers",
"timit_asr",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/sew-d-small-100k-timit | 26 | null | transformers | 7,559 | ---
license: apache-2.0
tags:
- automatic-speech-recognition
- timit_asr
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: sew-d-small-100k-timit
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofre... |
rajratnpranesh/DCS_sanskrit_bert | 69b6d784189fdd3176e2087303afaee66e828eda | 2021-05-20T03:52:51.000Z | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | rajratnpranesh | null | rajratnpranesh/DCS_sanskrit_bert | 26 | null | transformers | 7,560 | Entry not found |
shahrukhx01/roberta-base-squad2-boolq-baseline | ad3bde67e7d2489e15d519fadbeeae733ee91659 | 2021-09-28T18:18:26.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | shahrukhx01 | null | shahrukhx01/roberta-base-squad2-boolq-baseline | 26 | null | transformers | 7,561 | ## Multiple Prediction Heads
* ExtractiveQA Head
* Three Class Classification Head, classes => (yes, no, extra_qa) to answer binary questions or direct to ExtractiveQA Head
## BoolQ Validation dataset Evaluation: <br/>
support => 3270 <br/>
accuracy => 0.73 <br/>
macro f1 => 0.71
## SQuAD Validation dataset Evaluati... |
sultan/BioM-ELECTRA-Large-Generator | 4be3b63c6e32aaafeed9e1877a8f8b683a3a56d0 | 2021-05-24T21:07:58.000Z | [
"pytorch",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | sultan | null | sultan/BioM-ELECTRA-Large-Generator | 26 | null | transformers | 7,562 | # BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA
# Abstract
The impact of design choices on the performance
of biomedical language models recently
has been a subject for investigation. In
this paper, we empirically study biomedical
domain adaptation with large transformer ... |
tbrasil/classificador_de_atendimento_3_classes_v1.1 | c7825e99fb9b49e3f7b6ef33f020f799ac24568d | 2021-07-26T17:26:26.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | tbrasil | null | tbrasil/classificador_de_atendimento_3_classes_v1.1 | 26 | null | transformers | 7,563 | Entry not found |
yoshitomo-matsubara/bert-large-uncased-qnli | 6bf3fa14095da060773362e19be89bd7db46b4ca | 2021-05-29T21:33:19.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:qnli",
"transformers",
"qnli",
"glue",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-large-uncased-qnli | 26 | null | transformers | 7,564 | ---
language: en
tags:
- bert
- qnli
- glue
- torchdistill
license: apache-2.0
datasets:
- qnli
metrics:
- accuracy
---
`bert-large-uncased` fine-tuned on QNLI dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.research.google.com/github/yoshitomo-... |
gustavecortal/gpt-j-fr-covid-news | 397ecac9686c226e98af93c9b986e75be3510905 | 2022-03-10T10:05:27.000Z | [
"pytorch",
"gptj",
"text-generation",
"fr",
"dataset:gustavecortal/fr_covid_news",
"transformers",
"causal-lm",
"license:mit"
] | text-generation | false | gustavecortal | null | gustavecortal/gpt-j-fr-covid-news | 26 | 1 | transformers | 7,565 | ---
language: fr
license: mit
tags:
- causal-lm
- fr
datasets:
- gustavecortal/fr_covid_news
---
### GPT-J COVID-19 French News with 8-bit weights
This is a version of Cedille's GPT-J ([fr-boris](https://huggingface.co/gustavecortal/fr-boris-8bit)) with 6 billion parameters fine-tuned on [COVID-19 French News datas... |
aicryptogroup/distill-xlm-mrc | 41ba30c18793cb527db62b68b47c9e0881e25a4a | 2022-04-26T02:40:42.000Z | [
"pytorch",
"roberta",
"question-answering",
"vi",
"vn",
"en",
"dataset:squad",
"transformers",
"autotrain_compatible"
] | question-answering | false | aicryptogroup | null | aicryptogroup/distill-xlm-mrc | 26 | null | transformers | 7,566 | ---
language:
- vi
- vn
- en
tags:
- question-answering
- pytorch
datasets:
- squad
pipeline_tag: question-answering
metrics:
- squad
widget:
- text: "what is the capital of Vietnam ?"
context: "Keeping an ageless charm through centuries, Hanoi - the capital of Vietnam is famous not only for the Old ... |
BigSalmon/MASKGPT2 | 273e2105628f5a4ef264b86ee582bbd088c705a6 | 2022-03-23T19:26:53.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | BigSalmon | null | BigSalmon/MASKGPT2 | 26 | null | transformers | 7,567 | ```
original: sports teams are profitable for owners. [MASK], their valuations experience a dramatic uptick.
infill: sports teams are profitable for owners. ( accumulating vast sums / stockpiling treasure / realizing benefits / cashing in / registering robust financials / scoring on balance sheets ), their valuations ... |
gastronomia-para-to2/gastronomia_para_to2 | 71f14c3b2d495242c2d94d31a2714b6589b7c1c0 | 2022-06-23T14:55:10.000Z | [
"pytorch",
"gpt2",
"text-generation",
"es",
"transformers",
"generated_from_trainer",
"recipe-generation"
] | text-generation | false | gastronomia-para-to2 | null | gastronomia-para-to2/gastronomia_para_to2 | 26 | 1 | transformers | 7,568 | ---
language:
- es
tags:
- generated_from_trainer
- recipe-generation
widget:
- text: "<RECIPE_START> <INPUT_START> salmón <NEXT_INPUT> zumo de naranja <NEXT_INPUT> aceite de oliva <NEXT_INPUT> sal <NEXT_INPUT> pimienta <INPUT_END> <INGR_START>"
- text: "<RECIPE_START> <INPUT_START> harina <NEXT_INPUT> azúcar <NEX... |
azwierzc/visualbert-vqa-pl-v2 | 7b22112d72aa33d7a8c6040a4a8405f3df987163 | 2022-04-08T17:27:22.000Z | [
"pytorch",
"visual_bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | azwierzc | null | azwierzc/visualbert-vqa-pl-v2 | 26 | null | transformers | 7,569 | Entry not found |
agdsga/nezha-chinese-base-finetuned-product | df319d6a680c2dc1f9f83c81eeed8b471fee13fa | 2022-04-08T06:12:55.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-generation",
"transformers",
"generated_from_trainer",
"model-index"
] | text-generation | false | agdsga | null | agdsga/nezha-chinese-base-finetuned-product | 26 | null | transformers | 7,570 | ---
tags:
- generated_from_trainer
model-index:
- name: nezha-chinese-base-finetuned-product
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. -->
# nezha-chinese-base... |
vocab-transformers/distilbert-tokenizer_256k-MLM_best | bfef0b2f4f40bd88744cf1360ef42a5599c9c215 | 2022-04-11T11:16:06.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | vocab-transformers | null | vocab-transformers/distilbert-tokenizer_256k-MLM_best | 26 | null | transformers | 7,571 | # DistilBERT with 256k token embeddings
This model was initialized with a word2vec token embedding matrix with 256k entries, but these token embeddings were updated during MLM. The word2vec was trained on 100GB data from C4, MSMARCO, News, Wikipedia, S2ORC, for 3 epochs.
Then the model was trained on this dataset wit... |
nikhedward/bart-large-cnn-finetuned-multi-news | 6c150c04431d453a41e2492a3a425cee806cf9db | 2022-04-29T15:22:47.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"dataset:multi_news",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | nikhedward | null | nikhedward/bart-large-cnn-finetuned-multi-news | 26 | null | transformers | 7,572 | ---
license: mit
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-multi-news
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
args:... |
Helsinki-NLP/opus-mt-tc-big-sh-en | 052ec88282054d9eddfa0da15222852477182abe | 2022-06-01T13:01:15.000Z | [
"pytorch",
"marian",
"text2text-generation",
"bs_Latn",
"en",
"hr",
"sh",
"sr_Cyrl",
"sr_Latn",
"transformers",
"translation",
"opus-mt-tc",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tc-big-sh-en | 26 | null | transformers | 7,573 | ---
language:
- bs_Latn
- en
- hr
- sh
- sr_Cyrl
- sr_Latn
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-sh-en
results:
- task:
name: Translation hrv-eng
type: translation
args: hrv-eng
dataset:
name: flores101-devtest
type: flores_101
... |
Helsinki-NLP/opus-mt-tc-big-hu-en | 11be72afb7594e726e543badd3bd658922afe715 | 2022-06-01T13:01:06.000Z | [
"pytorch",
"marian",
"text2text-generation",
"en",
"hu",
"transformers",
"translation",
"opus-mt-tc",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-tc-big-hu-en | 26 | null | transformers | 7,574 | ---
language:
- en
- hu
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-hu-en
results:
- task:
name: Translation hun-eng
type: translation
args: hun-eng
dataset:
name: flores101-devtest
type: flores_101
args: hun eng devtest
metrics... |
chenshuangcufe/Bert-job | 8d613690c9d25ac4ab473f598ba6683ac24c3ec2 | 2022-04-21T08:10:11.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | chenshuangcufe | null | chenshuangcufe/Bert-job | 26 | null | transformers | 7,575 | Entry not found |
doc2query/msmarco-vietnamese-mt5-base-v1 | 1ac7b8c530c4dcbce052a0f1b7c2beca48ad21f5 | 2022-04-29T22:06:03.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"vi",
"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-vietnamese-mt5-base-v1 | 26 | 1 | transformers | 7,576 | ---
language: vi
datasets:
- unicamp-dl/mmarco
widget:
- text: "Python (phát âm tiếng Anh: /ˈpaɪθɑːn/) là một ngôn ngữ lập trình bậc cao cho các mục đích lập trình đa năng, do Guido van Rossum tạo ra và lần đầu ra mắt vào năm 1991. Python được thiết kế với ưu điểm mạnh là dễ đọc, dễ học và dễ nhớ. Python là ngôn n... |
TehranNLP-org/electra-base-sst2 | 53949b15b42995131562678a342f48d2280f3dcd | 2022-05-03T17:00:04.000Z | [
"pytorch",
"electra",
"text-classification",
"en",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | TehranNLP-org | null | TehranNLP-org/electra-base-sst2 | 26 | null | transformers | 7,577 | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SEED0042
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: SST2
type: ''
args: sst2
metrics:
- name: Accuracy
type: accurac... |
nbasatish/financial-pegasus | 1bd55e4aea4a0d7b76581c3f3a5ed738d968c909 | 2022-05-01T22:36:58.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | nbasatish | null | nbasatish/financial-pegasus | 26 | null | transformers | 7,578 | ---
license: apache-2.0
---
|
nikitast/multilang-classifier-roberta | 475e27c7ccf628507ea7218b86901ad1ecad7a46 | 2022-07-18T11:34:28.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"ru",
"uk",
"be",
"kk",
"az",
"hy",
"ka",
"he",
"en",
"de",
"dataset:open_subtitles",
"dataset:tatoeba",
"dataset:oscar",
"transformers",
"language classification"
] | text-classification | false | nikitast | null | nikitast/multilang-classifier-roberta | 26 | null | transformers | 7,579 | ---
language:
- ru
- uk
- be
- kk
- az
- hy
- ka
- he
- en
- de
tags:
- language classification
datasets:
- open_subtitles
- tatoeba
- oscar
---
# RoBERTa for Multilabel Language Classification
## Training
RoBERTa fine-tuned on small parts of Open Subtitles, Oscar and Tatoeba datasets (~9k samples per language).
Imp... |
Mathilda/T5-paraphrasing | 1ffe344dc45b713d3b212ac67ceba7739a1c215f | 2022-05-16T15:40:05.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | text2text-generation | false | Mathilda | null | Mathilda/T5-paraphrasing | 26 | null | transformers | 7,580 | ---
license: afl-3.0
---
|
FrGes/xlm-roberta-large-finetuned-EUJAV-datasetA | b2d12c1d77878c92576fd890ec40851946258dba | 2022-05-18T11:29:30.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | FrGes | null | FrGes/xlm-roberta-large-finetuned-EUJAV-datasetA | 26 | null | transformers | 7,581 | Fine-tuned model based on
#XLM-RoBERTa (large-sized model)
Data for finetuning:
Italian vaccine stance data: 781 training tweets and 281 evaluation tweets
#BibTeX entry and citation info
to be added |
microsoft/cvt-w24-384-22k | a9aa85d4952c0bf1531fdc878b8c04c8cbbb2ec8 | 2022-05-18T17:18:47.000Z | [
"pytorch",
"cvt",
"image-classification",
"dataset:imagenet-1k",
"arxiv:2103.15808",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/cvt-w24-384-22k | 26 | null | transformers | 7,582 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- src: https... |
fujiki/t5-large-en2ja | 8a3d74abae8d6ff3c4d99e757d1e4da17f419fa3 | 2022-05-21T14:30:08.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"license:cc-by-sa-3.0",
"autotrain_compatible"
] | text2text-generation | false | fujiki | null | fujiki/t5-large-en2ja | 26 | null | transformers | 7,583 | ---
license: cc-by-sa-3.0
---
|
ccdv/lsg-bart-base-4096-wcep | 203cea7c0c5a1cff5a721d625ddfa62661e563d1 | 2022-07-25T05:30:19.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:ccdv/WCEP-10",
"transformers",
"summarization",
"model-index",
"autotrain_compatible"
] | summarization | false | ccdv | null | ccdv/lsg-bart-base-4096-wcep | 26 | null | transformers | 7,584 | ---
language:
- en
tags:
- summarization
datasets:
- ccdv/WCEP-10
metrics:
- rouge
model-index:
- name: ccdv/lsg-bart-base-4096-wcep
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... |
ericntay/distilbert-base-uncased-finetuned-emotion | 6fcf9ab0769e52370ca903119ec5d3e925472d8c | 2022-05-26T16:51:22.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | ericntay | null | ericntay/distilbert-base-uncased-finetuned-emotion | 26 | null | transformers | 7,585 | ---
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... |
ddobokki/electra-small-sts-cross-encoder | ec59c0d95dbc48687edb445f9e86b2e4c4c39052 | 2022-05-31T07:52:44.000Z | [
"pytorch",
"electra",
"text-classification",
"ko",
"transformers",
"sentence_transformers",
"cross_encoder"
] | text-classification | false | ddobokki | null | ddobokki/electra-small-sts-cross-encoder | 26 | null | transformers | 7,586 | ---
language:
- ko
tags:
- sentence_transformers
- cross_encoder
---
# Example
```python
from sentence_transformers import CrossEncoder
model = CrossEncoder('ddobokki/electra-small-sts-cross-encoder')
model.predict(["그녀는 행복해서 웃었다.", "그녀는 웃겨서 눈물이 났다."])
-> 0.8206561
```
# Dataset
- KorSTS
- Train
- Test
- KLUE STS... |
rifkat/GPTuz | 2a7e6c05772bc155145b37cf904cc88fde2218de | 2022-06-09T09:13:55.000Z | [
"pytorch",
"tf",
"gpt2",
"text-generation",
"uz",
"transformers",
"Text Generation",
"PyTorch",
"TensorFlow",
"Transformers",
"mit",
"license:apache-2.0"
] | text-generation | false | rifkat | null | rifkat/GPTuz | 26 | null | transformers | 7,587 | ---
language:
- uz
tags:
- Text Generation
- PyTorch
- TensorFlow
- Transformers
- mit
- uz
- gpt2
license: apache-2.0
widget:
- text: "Covid-19 га қарши эмлаш бошланди,"
example_title: "Namuna 1"
- text: "Суъний интеллект энг ривожланган"
example_title: "Namuna 2"
---
<p><b>GPTuzmodel.</b>
GPTuz GPT-2 kichik mod... |
ghadeermobasher/Orignial-BlueBERT-NCBI | 76c755792659af70fe151823537327468666b713 | 2022-06-09T15:18:08.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Orignial-BlueBERT-NCBI | 26 | null | transformers | 7,588 | Entry not found |
ChainYo/segformer-b1-sidewalk | 571324ba0f685ab8304f1f3a89aec92724711021 | 2022-06-14T16:33:48.000Z | [
"pytorch",
"segformer",
"dataset:segments/sidewalk-semantic",
"arxiv:2105.15203",
"transformers",
"vision",
"image-segmentation",
"license:apache-2.0"
] | image-segmentation | false | ChainYo | null | ChainYo/segformer-b1-sidewalk | 26 | null | transformers | 7,589 | ---
license: apache-2.0
tags:
- vision
- image-segmentation
datasets:
- segments/sidewalk-semantic
---
# SegFormer (b1-sized) model fine-tuned on sidewalk-semantic dataset
SegFormer model fine-tuned on segments/sidewalk-semantic at resolution 512x512. It was introduced in the paper [SegFormer: Simple and Efficient De... |
Shaier/distilbert-base-uncased-continued_training-medqa | 10889756a9158acb28372809c661a4b98b5e80c4 | 2022-06-28T19:04:13.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | fill-mask | false | Shaier | null | Shaier/distilbert-base-uncased-continued_training-medqa | 26 | null | transformers | 7,590 | ---
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-continued_training-medqa
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. -->
# distil... |
PrimeQA/mt5-base-tydi-question-generator | ac1f94b893b071bff2eee5a26f5ef0a75513f846 | 2022-07-13T10:38:38.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | PrimeQA | null | PrimeQA/mt5-base-tydi-question-generator | 26 | null | transformers | 7,591 | ---
license: apache-2.0
---
# Model description
This is an [mt5-base](https://huggingface.co/google/mt5-base) model, finetuned to generate questions using [TyDi QA](https://huggingface.co/datasets/tydiqa) dataset. It was trained to take the context and answer as input to generate questions.
# Overview
*Language mod... |
djagatiya/ner-roberta-base-ontonotesv5-englishv4 | 28af6bc088b67380ed35c7eb3ef3a0320149acc1 | 2022-07-03T11:27:14.000Z | [
"pytorch",
"roberta",
"token-classification",
"dataset:djagatiya/ner-ontonotes-v5-eng-v4",
"transformers",
"autotrain_compatible"
] | token-classification | false | djagatiya | null | djagatiya/ner-roberta-base-ontonotesv5-englishv4 | 26 | null | transformers | 7,592 | ---
tags:
- token-classification
datasets:
- djagatiya/ner-ontonotes-v5-eng-v4
widget:
- text: "On September 1st George won 1 dollar while watching Game of Thrones."
---
# (NER) roberta-base : conll2012_ontonotesv5-english-v4
This `roberta-base` NER model was finetuned on `conll2012_ontonotesv5` version `english-v4... |
huggingtweets/dinidu | 670f083816d5fc3562d7ff6618d4a61989866fa2 | 2022-07-07T13:00:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/dinidu | 26 | null | transformers | 7,593 | ---
language: en
thumbnail: http://www.huggingtweets.com/dinidu/1657198765981/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 9... |
malteos/gpt2-xl-german-covid-19 | 1298d0cdc9d3af23ed07ef3125349e2de3e5edfc | 2022-07-08T13:48:32.000Z | [
"pytorch",
"gpt2",
"text-generation",
"de",
"transformers",
"license:mit"
] | text-generation | false | malteos | null | malteos/gpt2-xl-german-covid-19 | 26 | null | transformers | 7,594 | ---
license: mit
language: de
widget:
- text: "Noch Wochen nach einer Erkrankung an COVID-19 können "
---
# German Covid-19 GPT2-XL (1.5B)
- Covid-19 specific version of [`malteos/gpt2-xl-wechsel-german`](https://huggingface.co/malteos/gpt2-xl-wechsel-german)
- Fine-tuned on 2 GB text from OSCAR filtered for covid r... |
AndyChiang/bert-test | 2d299bfe9d01b27ccbadd6ae0f643643604c35a8 | 2022-07-11T05:50:10.000Z | [
"pytorch",
"tf",
"bert",
"fill-mask",
"transformers",
"generated_from_keras_callback",
"model-index",
"autotrain_compatible"
] | fill-mask | false | AndyChiang | null | AndyChiang/bert-test | 26 | null | transformers | 7,595 | ---
tags:
- generated_from_keras_callback
model-index:
- name: bert-test
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# bert-test
This model was trained from scrat... |
p-christ/testrepo | a205a3f1ee51f9b1784d92a71b31caab4d7f1d7e | 2022-07-11T15:55:20.000Z | [
"pytorch",
"t5",
"text2text-generation",
"generic"
] | text2text-generation | false | p-christ | null | p-christ/testrepo | 26 | null | generic | 7,596 | ---
tags:
- text2text-generation
library_name: generic
---
random test repo |
abecode/t5-small-finetuned-emo20q | 9606e2a03500b44c351be05ae9c6abe1a71e389e | 2022-07-11T17:56:42.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | abecode | null | abecode/t5-small-finetuned-emo20q | 26 | 1 | transformers | 7,597 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-emo20q
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-small-... |
Vikasbhandari/wav2vec2-train | 1e017454b6d3fdcae5104b5a1ac5a3411caa8091 | 2022-07-12T11:51:48.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2010.11430",
"arxiv:2006.11477",
"transformers",
"speech",
"audio",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Vikasbhandari | null | Vikasbhandari/wav2vec2-train | 26 | null | transformers | 7,598 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
model-index:
- name: wav2vec2-large-960h-lv60
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: LibriS... |
thusken/nb-bert-base-user-needs | 688bd9f5003ea4d16f66b01eed6a8ae4c2581715 | 2022-07-15T10:15:43.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:cc-by-4.0",
"model-index"
] | text-classification | false | thusken | null | thusken/nb-bert-base-user-needs | 26 | null | transformers | 7,599 | ---
license: cc-by-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: nb-bert-base-user-needs
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... |
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