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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
pszemraj/bigbird-pegasus-large-K-booksum | c3138586bd440f4f67f38a2dbb81a00e10a21da3 | 2022-07-15T08:54:09.000Z | [
"pytorch",
"bigbird_pegasus",
"text2text-generation",
"en",
"dataset:kmfoda/booksum",
"arxiv:2105.08209",
"transformers",
"summarization",
"summarisation",
"summary",
"notes",
"bigbird_pegasus_",
"pegasus",
"bigbird",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | summarization | false | pszemraj | null | pszemraj/bigbird-pegasus-large-K-booksum | 172 | 0 | transformers | 3,800 | ---
language:
- en
tags:
- summarization
- summarisation
- summary
- notes
- bigbird_pegasus_
- pegasus
- bigbird
license: apache-2.0
datasets:
- kmfoda/booksum
metrics:
- rouge
widget:
- text: large earthquakes along a given fault segment do not occur at random intervals
because it takes time to accumulate the str... |
UBC-NLP/ptsm_t5_paraphraser | 95d01b08b095d9057388c694f7cb133dc9b4a97d | 2022-07-05T18:34:19.000Z | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:2204.04611",
"transformers",
"license:cc-by-nc-3.0",
"autotrain_compatible"
] | text2text-generation | false | UBC-NLP | null | UBC-NLP/ptsm_t5_paraphraser | 172 | null | transformers | 3,801 | ---
license: cc-by-nc-3.0
---
# T5-base model trained for text paraphrase
You can load this model by:
```python
from transformers import T5ForConditionalGeneration,T5TokenizerFast
model = T5ForConditionalGeneration.from_pretrained(model_name_or_path)
tokenizer = T5TokenizerFast.from_pretrained(model_name_or_path)
`... |
webshop/il_search_bart | 982e94251ef9e9da0a7d35b10011866bbc94adf6 | 2022-06-16T00:03:31.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | webshop | null | webshop/il_search_bart | 172 | null | transformers | 3,802 | Entry not found |
dminiotas05/distilbert-base-uncased-finetuned-ft650_10class | 4ebde7f138a1023af09aebad251a20a783a035d6 | 2022-07-08T14:58:07.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | dminiotas05 | null | dminiotas05/distilbert-base-uncased-finetuned-ft650_10class | 172 | null | transformers | 3,803 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-ft650_10class
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... |
DeepChem/ChemBERTa-77M-MTR | 66b895cab8adebea0cb59a8effa66b2020f204ca | 2022-01-20T17:55:55.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | DeepChem | null | DeepChem/ChemBERTa-77M-MTR | 171 | 1 | transformers | 3,804 | Entry not found |
csebuetnlp/mT5_m2o_english_crossSum | 978a27fe57143fd862224d2f3c46bfa7d9cf8a7b | 2022-04-22T15:06:41.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"am",
"ar",
"az",
"bn",
"my",
"zh",
"en",
"fr",
"gu",
"ha",
"hi",
"ig",
"id",
"ja",
"rn",
"ko",
"ky",
"mr",
"ne",
"om",
"ps",
"fa",
"pcm",
"pt",
"pa",
"ru",
"gd",
"sr",
"si",
"so",
"es",
"sw",
"ta",
"te... | summarization | false | csebuetnlp | null | csebuetnlp/mT5_m2o_english_crossSum | 171 | null | transformers | 3,805 | ---
tags:
- summarization
- mT5
language:
- am
- ar
- az
- bn
- my
- zh
- en
- fr
- gu
- ha
- hi
- ig
- id
- ja
- rn
- ko
- ky
- mr
- ne
- om
- ps
- fa
- pcm
- pt
- pa
- ru
- gd
- sr
- si
- so
- es
- sw
- ta
- te
- th
- ti
- tr
- uk
- ur
- uz
- vi
- cy
- yo
licenses:
- cc-by-nc-sa-4.0
widget:
- text: "Videos that say a... |
microsoft/markuplm-large | eb3050bd84ff27279fe2669b0fafbc54805c3cb3 | 2022-01-11T12:33:09.000Z | [
"pytorch",
"markuplm",
"arxiv:2110.08518",
"transformers"
] | null | false | microsoft | null | microsoft/markuplm-large | 171 | 4 | transformers | 3,806 | # MarkupLM
**Multimodal (text +markup language) pre-training for [Document AI](https://www.microsoft.com/en-us/research/project/document-ai/)**
## Introduction
MarkupLM is a simple but effective multi-modal pre-training method of text and markup language for visually-rich document understanding and information extra... |
cardiffnlp/tweet-topic-19-multi | 307927c515fadb84eec00da911e2bbdaef3ffeef | 2022-06-09T10:35:40.000Z | [
"pytorch",
"tf",
"roberta",
"text-classification",
"arxiv:2202.03829",
"transformers"
] | text-classification | false | cardiffnlp | null | cardiffnlp/tweet-topic-19-multi | 171 | null | transformers | 3,807 | # tweet-topic-19-multi
This is a roBERTa-base model trained on ~90m tweets until the end of 2019 (see [here](https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m)), and finetuned for multi-label topic classification on a corpus of 11,267 tweets.
The original roBERTa-base model can be found [here](https://h... |
IDEA-CCNL/Randeng-Pegasus-238M-Chinese | 82892ea47cd837c97a8d821d7198331195e0d0c5 | 2022-06-30T07:00:00.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"zh",
"arxiv:1912.08777",
"transformers",
"summarization",
"chinese",
"autotrain_compatible"
] | summarization | false | IDEA-CCNL | null | IDEA-CCNL/Randeng-Pegasus-238M-Chinese | 171 | 2 | transformers | 3,808 | ---
language: zh
tags:
- summarization
- chinese
inference: False
---
IDEA-CCNL/Randeng-Pegasus-238M-Chinese model (Chinese)，codes has merged into [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)
The 523M million parameter randeng_pegasus_large model, training with sampled gap sentence ratios on 180G ... |
tahercoolguy/gpt-neox-bit | badab2056f28157226af57e2206991266787fedd | 2022-07-22T12:52:33.000Z | [
"pytorch",
"gpt_neox",
"text-generation",
"transformers",
"license:apache-2.0"
] | text-generation | false | tahercoolguy | null | tahercoolguy/gpt-neox-bit | 171 | null | transformers | 3,809 | ---
license: apache-2.0
---
|
TehranNLP-org/bert-base-uncased-cls-sst2 | 39e787510bf6883a49951d9ac50107e2b909e632 | 2022-05-01T11:44:45.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"transformers"
] | text-classification | false | TehranNLP-org | null | TehranNLP-org/bert-base-uncased-cls-sst2 | 170 | null | transformers | 3,810 | Entry not found |
allenai/unifiedqa-v2-t5-3b-1251000 | b1a4a8f236b9f3717d0083235fcc5a688649c2d2 | 2022-02-22T05:38:59.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/unifiedqa-v2-t5-3b-1251000 | 170 | null | transformers | 3,811 | # Further details: https://github.com/allenai/unifiedqa
|
gagan3012/ViTGPT2_vizwiz | 4a1d4301fb350671d479c198edef15b490ab9509 | 2022-02-07T05:54:26.000Z | [
"pytorch",
"vision-encoder-decoder",
"transformers",
"generated_from_trainer",
"image-to-text",
"model-index"
] | image-to-text | false | gagan3012 | null | gagan3012/ViTGPT2_vizwiz | 170 | null | transformers | 3,812 | ---
tags:
- generated_from_trainer
- image-to-text
model-index:
- name: ViTGPT2_vizwiz
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. -->
# ViTGPT2_vizwiz
This mod... |
ghanashyamvtatti/roberta-fake-news | 3ac92babef4d120bb478b789c00d48225b96008a | 2021-05-20T16:33:04.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | ghanashyamvtatti | null | ghanashyamvtatti/roberta-fake-news | 170 | null | transformers | 3,813 | A fake news detector using RoBERTa.
Dataset: https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset
Training involved using hyperparameter search with 10 trials. |
huggingtweets/normmacdonald | 06a7e2866691801be88f21f0b1270872ddbf5c25 | 2021-05-22T16:47:41.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/normmacdonald | 170 | null | transformers | 3,814 | ---
language: en
thumbnail: https://www.huggingtweets.com/normmacdonald/1617162362414/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/1281990037/... |
nateraw/vit-base-patch16-224-cifar10 | b55eeb4221d3a568f627078ed6f27b967810be3d | 2022-01-28T10:22:01.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:cifar10",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | nateraw | null | nateraw/vit-base-patch16-224-cifar10 | 170 | 3 | transformers | 3,815 | ---
tags:
- image-classification
- vision
- pytorch
license: apache-2.0
datasets:
- cifar10
metrics:
- accuracy
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
---
# Vision Transformer Fine Tuned on CIFAR10
Vision Transformer (ViT) model pre-trained on... |
vitouphy/wav2vec2-xls-r-300m-phoneme | ac268b1bf8433073b39e5f16925bf631f05dfa10 | 2022-05-19T07:13:47.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | vitouphy | null | vitouphy/wav2vec2-xls-r-300m-phoneme | 170 | null | transformers | 3,816 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-xls-r-300m-phoneme
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. -->
# wav2vec... |
MultiTrickFox/bloom-2b5_Zen | a80e3ea3fcff6a5a098f9fba294cab4d0e43fa43 | 2022-07-16T11:00:12.000Z | [
"pytorch",
"bloom",
"text-generation",
"transformers"
] | text-generation | false | MultiTrickFox | null | MultiTrickFox/bloom-2b5_Zen | 170 | null | transformers | 3,817 | #####
## Bloom2.5B Zen ##
#####
Bloom (2.5 B) Scientific Model fine-tuned on Zen knowledge
#####
## Usage ##
#####
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MultiTrickFox/bloom-2b5_Zen")
model = AutoModelForCausalLM.from_pretra... |
Bhumika/roberta-base-finetuned-sst2 | eee69c5668a64e30f2e9cc61d3975afc724a7880 | 2021-10-25T06:17:25.000Z | [
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | Bhumika | null | Bhumika/roberta-base-finetuned-sst2 | 169 | 3 | transformers | 3,818 | ---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-sst2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- name: Accuracy
type: accu... |
Helsinki-NLP/opus-mt-zh-de | 04388d8cb09ccbf0fda70feeeec41b7d85ca3ec4 | 2020-08-21T14:42:52.000Z | [
"pytorch",
"marian",
"text2text-generation",
"zh",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-zh-de | 169 | null | transformers | 3,819 | ---
language:
- zh
- de
tags:
- translation
license: apache-2.0
---
### zho-deu
* source group: Chinese
* target group: German
* OPUS readme: [zho-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-deu/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hang... |
KoichiYasuoka/roberta-small-japanese-luw-upos | b493f7d03078d5c0d9ce3f4c29192dc831dd8180 | 2022-05-24T06:25:43.000Z | [
"pytorch",
"roberta",
"token-classification",
"ja",
"dataset:universal_dependencies",
"transformers",
"japanese",
"pos",
"dependency-parsing",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | false | KoichiYasuoka | null | KoichiYasuoka/roberta-small-japanese-luw-upos | 169 | null | transformers | 3,820 | ---
language:
- "ja"
tags:
- "japanese"
- "token-classification"
- "pos"
- "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。"
---
# roberta-small-japanese-luw-upos
## Model Description
This is a RoBERTa model ... |
deepklarity/poster2plot | 749bdc7871ec8f5ffec753f21448cdc2bc1a1a27 | 2021-11-22T19:56:30.000Z | [
"pytorch",
"vision-encoder-decoder",
"en",
"transformers",
"image-classification",
"image-captioning"
] | image-classification | false | deepklarity | null | deepklarity/poster2plot | 169 | 1 | transformers | 3,821 | ---
language: en
tags:
- image-classification
- image-captioning
---
# Poster2Plot
An image captioning model to generate movie/t.v show plot from poster. It generates decent plots but is no way perfect. We are still working on improving the model.
## Live demo on Hugging Face Spaces: https://huggingface.co/spaces/d... |
huggingtweets/atlassian | 43a6eceff7358412812946c5d465edd0aa17e36e | 2021-06-17T00:20:35.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/atlassian | 169 | null | transformers | 3,822 | ---
language: en
thumbnail: https://www.huggingtweets.com/atlassian/1623889197185/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; widt... |
navteca/electra-base-squad2 | 1983e4c58b41d0a967e957d5df8579f85543d861 | 2021-03-10T15:30:09.000Z | [
"pytorch",
"electra",
"question-answering",
"en",
"dataset:squad_v2",
"transformers",
"license:mit",
"autotrain_compatible"
] | question-answering | false | navteca | null | navteca/electra-base-squad2 | 169 | null | transformers | 3,823 | ---
datasets:
- squad_v2
language: en
license: mit
pipeline_tag: question-answering
tags:
- electra
- question-answering
---
# Electra base model for QA (SQuAD 2.0)
This model uses [electra-base](https://huggingface.co/google/electra-base-discriminator).
## Training Data
The models have been trained on the [SQuAD 2.0... |
ptaszynski/yacis-electra-small-japanese | 01f2eca3bdbaf8d536ba7b74fb33fd2c9b853ed4 | 2022-01-13T01:43:17.000Z | [
"pytorch",
"ja",
"dataset:YACIS corpus",
"transformers",
"license:cc-by-sa-4.0"
] | null | false | ptaszynski | null | ptaszynski/yacis-electra-small-japanese | 169 | 2 | transformers | 3,824 | ---
language: ja
license: cc-by-sa-4.0
datasets:
- YACIS corpus
---
# yacis-electra-small
This is [ELECTRA](https://github.com/google-research/electra) Small model for Japanese pretrained on 354 million sentences / 5.6 billion words of [YACIS](https://github.com/ptaszynski/yacis-corpus) blog corpus.
The corpus ... |
DTAI-KULeuven/robbertje-1-gb-merged | 2b0bfb1015068ad0aee8d78789aba5f5a857353a | 2022-02-24T09:56:43.000Z | [
"pytorch",
"roberta",
"fill-mask",
"nl",
"dataset:oscar",
"dataset:oscar (NL)",
"dataset:dbrd",
"dataset:lassy-ud",
"dataset:europarl-mono",
"dataset:conll2002",
"arxiv:2101.05716",
"transformers",
"Dutch",
"Flemish",
"RoBERTa",
"RobBERT",
"RobBERTje",
"license:mit",
"autotrain_c... | fill-mask | false | DTAI-KULeuven | null | DTAI-KULeuven/robbertje-1-gb-merged | 168 | null | transformers | 3,825 | ---
language: "nl"
thumbnail: "https://github.com/iPieter/RobBERT/raw/master/res/robbert_logo.png"
tags:
- Dutch
- Flemish
- RoBERTa
- RobBERT
- RobBERTje
license: mit
datasets:
- oscar
- oscar (NL)
- dbrd
- lassy-ud
- europarl-mono
- conll2002
widget:
- text: "Hallo, ik ben RobBERTje, een gedistilleerd <mask> taalmode... |
cambridgeltl/trans-encoder-cross-simcse-bert-base | 9a73024eee6719e7622a29d6d2b31c06611bb0fb | 2021-11-26T18:24:44.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | cambridgeltl | null | cambridgeltl/trans-encoder-cross-simcse-bert-base | 168 | null | transformers | 3,826 | Entry not found |
imjeffhi/pokemon_classifier | 83deabd5a137d78fbd62b4c2b11595a888cf3fa6 | 2022-01-01T00:55:49.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers"
] | image-classification | false | imjeffhi | null | imjeffhi/pokemon_classifier | 168 | 3 | transformers | 3,827 | [](https://ainize.web.app/redirect?git_repo=https://github.com/imjeffhi4/pokemon-classifier)
# Pokémon Classifier
# Intro
A fine-tuned version of ViT-base on a collected set of Pokémon images. You can read more about the model [here](https://medium.c... |
openai/imagegpt-medium | 62aa3f00eb16af0e9e7f7d02b2db9c3fa625ed51 | 2022-06-30T06:46:11.000Z | [
"pytorch",
"imagegpt",
"dataset:imagenet-21k",
"transformers",
"vision",
"license:apache-2.0"
] | null | false | openai | null | openai/imagegpt-medium | 168 | 0 | transformers | 3,828 | ---
license: apache-2.0
tags:
- vision
datasets:
- imagenet-21k
---
# ImageGPT (medium-sized model)
ImageGPT (iGPT) model pre-trained on ImageNet ILSVRC 2012 (14 million images, 21,843 classes) at resolution 32x32. It was introduced in the paper [Generative Pretraining from Pixels](https://cdn.openai.com/papers/Gene... |
sentence-transformers/msmarco-MiniLM-L12-cos-v5 | ac9b7aaeea782db12fcd41670de2092ecce4ff65 | 2022-06-15T23:55:59.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/msmarco-MiniLM-L12-cos-v5 | 168 | null | sentence-transformers | 3,829 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# msmarco-MiniLM-L12-cos-v5
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and was designed for **sem... |
toastynews/electra-hongkongese-base-discriminator | 6b179082fdd82e255f3d37ff97a83bbe8174a227 | 2020-07-07T17:55:51.000Z | [
"pytorch",
"tf",
"electra",
"pretraining",
"yue",
"transformers",
"license:apache-2.0"
] | null | false | toastynews | null | toastynews/electra-hongkongese-base-discriminator | 168 | null | transformers | 3,830 | ---
language: yue
license: apache-2.0
metrics:
- DRCD
- openrice-senti
- lihkg-cat
- wordshk-sem
---
# ELECTRA Hongkongese Base
## Model description
ELECTRA trained exclusively with data from Hong Kong. A signaficant amount of Hongkongese/Cantonese/Yue is included in the training data.
## Intended uses & limitation... |
yoshitomo-matsubara/bert-base-uncased-qqp | 6ac7d79763a5f90f027981122555b03bcf394e93 | 2021-05-29T21:52:35.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:qqp",
"transformers",
"qqp",
"glue",
"torchdistill",
"license:apache-2.0"
] | text-classification | false | yoshitomo-matsubara | null | yoshitomo-matsubara/bert-base-uncased-qqp | 168 | null | transformers | 3,831 | ---
language: en
tags:
- bert
- qqp
- glue
- torchdistill
license: apache-2.0
datasets:
- qqp
metrics:
- f1
- accuracy
---
`bert-base-uncased` fine-tuned on QQP dataset, using [***torchdistill***](https://github.com/yoshitomo-matsubara/torchdistill) and [Google Colab](https://colab.research.google.com/github/yoshitomo... |
microsoft/resnet-34 | 4eb25387d2fc7c0108695bde3a590faa63132e22 | 2022-07-01T17:33:37.000Z | [
"pytorch",
"tf",
"resnet",
"image-classification",
"dataset:imagenet-1k",
"arxiv:1512.03385",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | microsoft | null | microsoft/resnet-34 | 168 | null | transformers | 3,832 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-1k
---
# ResNet-34 v1.5
ResNet model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) by He et al.
Disclaimer: The team ... |
LiYuan/amazon-query-product-ranking | 3496770750474054cbc36156f260683a3b56603b | 2022-04-28T13:09:08.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | LiYuan | null | LiYuan/amazon-query-product-ranking | 168 | null | transformers | 3,833 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-mnli-amazon-query-shopping
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and ... |
PrimeQA/tydiqa-boolean-question-classifier | 3a86131ea15cce3baeabba78cb64d0d35d373f67 | 2022-06-28T20:19:31.000Z | [
"pytorch",
"bert",
"text-classification",
"arxiv:1810.04805",
"arxiv:2206.08441",
"transformers",
"license:apache-2.0"
] | text-classification | false | PrimeQA | null | PrimeQA/tydiqa-boolean-question-classifier | 168 | null | transformers | 3,834 | ---
license: apache-2.0
---
## Model description
A question type classification model based on multilingual BERT.
The question type classifier takes as input the question, and returns a label that distinguishes between boolean and short answer extractive questions.
The model was initialized with [bert-base-multili... |
sijunhe/nezha-base-wwm | 629e6589f8a820e9622129e28d0c8625515de299 | 2022-06-24T03:55:20.000Z | [
"pytorch",
"nezha",
"fill-mask",
"arxiv:1909.00204",
"transformers",
"license:afl-3.0",
"autotrain_compatible"
] | fill-mask | false | sijunhe | null | sijunhe/nezha-base-wwm | 168 | null | transformers | 3,835 | ---
license: afl-3.0
---
**Please use 'Bert' related tokenizer classes and 'Nezha' related model classes**
[NEZHA: Neural Contextualized Representation for Chinese Language Understanding](https://arxiv.org/abs/1909.00204)
Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jian... |
lewiswu1209/Winnie | bfc6cdfebe4c203d3d24560dc0b241e800c54caa | 2022-07-27T17:07:55.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"license:mit"
] | text-generation | false | lewiswu1209 | null | lewiswu1209/Winnie | 168 | null | transformers | 3,836 | ---
license: mit
---
|
akshatpandeyme/DialoGPT-small-AnyaBot | c8132ec6356dbceb9157e3540da92a4fc639babb | 2022-07-27T06:12:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | akshatpandeyme | null | akshatpandeyme/DialoGPT-small-AnyaBot | 168 | null | transformers | 3,837 | ---
tags:
- conversational
---
# Anya conv. bot |
Helsinki-NLP/opus-mt-ar-ru | 4be9d95f8445c11b9f25fd6d128dd57cc38ce152 | 2021-01-18T07:47:44.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ar",
"ru",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ar-ru | 167 | null | transformers | 3,838 | ---
language:
- ar
- ru
tags:
- translation
license: apache-2.0
---
### ara-rus
* source group: Arabic
* target group: Russian
* OPUS readme: [ara-rus](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-rus/README.md)
* model: transformer
* source language(s): apc ara arz
* target langua... |
PlanTL-GOB-ES/roberta-base-ca | 94aef5c4319113211ed8860eb08eb13a862bd0fd | 2021-11-09T09:32:51.000Z | [
"pytorch",
"roberta",
"fill-mask",
"ca",
"transformers",
"masked-lm",
"BERTa",
"catalan",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | PlanTL-GOB-ES | null | PlanTL-GOB-ES/roberta-base-ca | 167 | 2 | transformers | 3,839 | ---
language: "ca"
tags:
- masked-lm
- BERTa
- catalan
widget:
- text: "El Català és una llengua molt <mask>."
- text: "Salvador Dalí va viure a <mask>."
- text: "La Costa Brava té les millors <mask> d'Espanya."
- text: "El cacaolat és un batut de <mask>."
- text: "<mask> és la capital de la Garrotxa."
- text: "Vaig al... |
datummd/NCBI_BC5CDR_disease | dc3c67689f98311940b9812352a624695554857f | 2021-08-31T13:59:31.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"dataset:ncbi_disease",
"dataset:BC5CDR-diseases",
"dataset:LitCOVID-pubtator",
"transformers",
"BioBERT",
"Diseases",
"NER",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | datummd | null | datummd/NCBI_BC5CDR_disease | 167 | 4 | transformers | 3,840 | ---
language:
- en
tags:
- BioBERT
- Diseases
- NER
license: apache-2.0
datasets:
- ncbi_disease
- BC5CDR-diseases
- LitCOVID-pubtator
---
BioBERT model fine-tuned in NER task with BC5CDR-diseases and NCBI-diseases corpus along with selected pubtator annotations from LitCOVID dataset
This was fine-tuned in order to us... |
mse30/bart-base-finetuned-pubmed | 2dcf6798d3889087bf314087dfc84a22c92e26d1 | 2021-10-14T15:19:57.000Z | [
"pytorch",
"bart",
"text2text-generation",
"dataset:scientific_papers",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | mse30 | null | mse30/bart-base-finetuned-pubmed | 167 | null | transformers | 3,841 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: bart-base-finetuned-pubmed
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific... |
praeclarum/cuneiform | df2918a9626a4c09fb82acc73fdbd409d654cfb2 | 2022-07-20T02:27:31.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"cuneiform",
"akkadian",
"sumerian",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | praeclarum | null | praeclarum/cuneiform | 167 | null | transformers | 3,842 | ---
license: mit
tags:
- cuneiform
- akkadian
- sumerian
---
# Sumerian and Akkadian Cuneiform Language Translator
This is a translation network that understands Sumerian and Akkadian languages written in cuneiform.
It was trained on cuneiform transcribed in the CDLI ATF format. For example:
```text
translate Akkad... |
Bman/DialoGPT-medium-shrek | e094faecd63fc4c0b604ea73b30425a5853d8fd0 | 2022-07-25T02:15:16.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Bman | null | Bman/DialoGPT-medium-shrek | 167 | null | transformers | 3,843 | ---
tags:
- conversational
---
# Shrek DialoGPT Model |
Alvenir/wav2vec2-base-da | 912002487cffc16dbedcad24db521596a05ef33c | 2021-11-28T11:35:11.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"da",
"transformers",
"speech",
"license:apache-2.0"
] | null | false | Alvenir | null | Alvenir/wav2vec2-base-da | 166 | 4 | transformers | 3,844 | ---
language: da
tags:
- speech
license: apache-2.0
---
# Wav2vec2-base for Danish
This wav2vec2-base model has been pretrained on ~1300 hours of danish speech data. The pretraining data consists of podcasts and audiobooks and is unfortunately not public available. However, we were allowed to distribute the pretrained... |
HooshvareLab/roberta-fa-zwnj-base-ner | eb045188128311055e23e2ac0941e76071fcdbd6 | 2021-05-20T11:55:34.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"token-classification",
"fa",
"transformers",
"autotrain_compatible"
] | token-classification | false | HooshvareLab | null | HooshvareLab/roberta-fa-zwnj-base-ner | 166 | null | transformers | 3,845 | ---
language: fa
---
# RobertaNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wik... |
bespin-global/klue-bert-base-aihub-mrc | bce73303f9411910709d5fcf097715446c047344 | 2022-06-18T05:09:55.000Z | [
"pytorch",
"bert",
"question-answering",
"ko",
"dataset:aihub",
"transformers",
"mrc",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | question-answering | false | bespin-global | null | bespin-global/klue-bert-base-aihub-mrc | 166 | 1 | transformers | 3,846 | ---
language: ko
tags:
- bert
- mrc
datasets:
- aihub
license: cc-by-nc-4.0
---
## Demo
- [https://huggingface.co/spaces/bespin-global/Bespin-QuestionAnswering](https://huggingface.co/spaces/bespin-global/Bespin-QuestionAnswering)
## Finetuning
- Pretrain Model : [klue/bert-base](https://github.com/KLUE-benchmark/KL... |
deep-learning-analytics/segformer_semantic_segmentation | 398ff9faf7ef7379bb0cd96107efbcd19d2b4903 | 2022-01-04T12:25:46.000Z | [
"pytorch",
"segformer",
"transformers"
] | null | false | deep-learning-analytics | null | deep-learning-analytics/segformer_semantic_segmentation | 166 | null | transformers | 3,847 | Entry not found |
facebook/wav2vec2-xls-r-1b-en-to-15 | b072afc9a7ed212179ac4fe2755287b5e65dc2c5 | 2022-05-26T22:27:12.000Z | [
"pytorch",
"speech-encoder-decoder",
"automatic-speech-recognition",
"multilingual",
"en",
"de",
"tr",
"fa",
"sv",
"mn",
"zh",
"cy",
"ca",
"sl",
"et",
"id",
"ar",
"ta",
"lv",
"ja",
"dataset:common_voice",
"dataset:multilingual_librispeech",
"dataset:covost2",
"arxiv:211... | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-xls-r-1b-en-to-15 | 166 | null | transformers | 3,848 | ---
language:
- multilingual
- en
- de
- tr
- fa
- sv
- mn
- zh
- cy
- ca
- sl
- et
- id
- ar
- ta
- lv
- ja
datasets:
- common_voice
- multilingual_librispeech
- covost2
tags:
- speech
- xls_r
- automatic-speech-recognition
- xls_r_translation
pipeline_tag: automatic-speech-recognition
license: apache-2.0
widget:
- e... |
felixhusen/poem | 86fdf8a8870ca99cb9a5aabea2a2032bfc8b6491 | 2021-05-21T16:01:12.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | felixhusen | null | felixhusen/poem | 166 | null | transformers | 3,849 | Entry not found |
projectaligned/gpt2-xl-reddit-writingprompts-behavior-cloning | c8d27145b10de890168e638b9139c9628fbbc9de | 2021-05-23T11:41:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | projectaligned | null | projectaligned/gpt2-xl-reddit-writingprompts-behavior-cloning | 166 | null | transformers | 3,850 | _deprecated_
This model is fine-tuned on data from https://www.reddit.com/r/WritingPrompts/
- The model is based on gpt2-xl
- The prompt responses to the top 1000 prompts (by upvote) are used to fine-tune the model. |
sagorsarker/codeswitch-hineng-lid-lince | 69ccbc5d4f9c8d066dd76f7cdb4e376aa63187ac | 2021-05-19T01:00:45.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"hi",
"en",
"dataset:lince",
"transformers",
"codeswitching",
"hindi-english",
"language-identification",
"license:mit",
"autotrain_compatible"
] | token-classification | false | sagorsarker | null | sagorsarker/codeswitch-hineng-lid-lince | 166 | null | transformers | 3,851 | ---
language:
- hi
- en
datasets:
- lince
license: mit
tags:
- codeswitching
- hindi-english
- language-identification
---
# codeswitch-hineng-lid-lince
This is a pretrained model for **language identification** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
This model is train... |
vanilladucky/Friends_chatting_bot_redefined | d317a87fed7ccf6778ef530c9607266ce15294a6 | 2022-03-20T10:08:19.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | vanilladucky | null | vanilladucky/Friends_chatting_bot_redefined | 166 | null | transformers | 3,852 | ---
tags:
- conversational
---
# My Awesome Model
|
Felix92/doctr-dummy-torch-crnn-vgg16-bn | 0063b3cd672db5586e093b3f8f33ebde051d1707 | 2022-05-25T21:34:04.000Z | [
"pytorch",
"en",
"transformers",
"image-to-text"
] | image-to-text | false | Felix92 | null | Felix92/doctr-dummy-torch-crnn-vgg16-bn | 166 | null | transformers | 3,853 |
---
language: en
pipeline_tag: image-to-text
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/... |
patrickvonplaten/hubert-xlarge-ls960-ft-4-gram | bf7facb778dd4a9613a5d936a726524e2706b372 | 2022-05-23T11:02:46.000Z | [
"pytorch",
"hubert",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"transformers",
"audio",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/hubert-xlarge-ls960-ft-4-gram | 166 | 2 | transformers | 3,854 | ---
language: en
datasets:
- librispeech_asr
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
license: apache-2.0
widget:
- example_title: Librispeech sample 1
src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
- example_title: Librispeech sample 2
src: https://cdn-media.huggingface.... |
ArthurZ/jukebox-5b-lyrics | 2de0fe8b3a95105ef4138ce7d946e930ee029df7 | 2022-07-26T06:02:43.000Z | [
"pytorch",
"jukebox",
"en",
"arxiv:2005.00341",
"transformers",
"MusicGeneration"
] | null | false | ArthurZ | null | ArthurZ/jukebox-5b-lyrics | 166 | 4 | transformers | 3,855 | ---
language:
- en
tags:
- MusicGeneration
---
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICEN... |
pyronear/rexnet1_0x | 689637bf1a679965d4be6ac94de3a0ddcab9401f | 2022-07-17T23:45:55.000Z | [
"pytorch",
"onnx",
"dataset:pyronear/openfire",
"arxiv:2007.00992",
"transformers",
"image-classification",
"license:apache-2.0"
] | image-classification | false | pyronear | null | pyronear/rexnet1_0x | 166 | null | transformers | 3,856 | ---
license: apache-2.0
tags:
- image-classification
- pytorch
- onnx
datasets:
- pyronear/openfire
---
# ReXNet-1.0x model
Pretrained on a dataset for wildfire binary classification (soon to be shared). The ReXNet architecture was introduced in [this paper](https://arxiv.org/pdf/2007.00992.pdf).
## Model descript... |
Yuetian/bert-base-uncased-finetuned-plutchik-emotion | d1f799821dc5bd723b98d52501f3c6f8aa42893c | 2022-07-25T04:41:30.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"license:mit"
] | text-classification | false | Yuetian | null | Yuetian/bert-base-uncased-finetuned-plutchik-emotion | 166 | null | transformers | 3,857 | ---
license: mit
---
|
ivan-savchuk/cross-encoder-ms-marco-MiniLM-L-12-v2-tuned_mediqa-v1 | f1cf7d1a13fd9d331784f8825adff0161e26670e | 2022-07-28T12:45:53.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | ivan-savchuk | null | ivan-savchuk/cross-encoder-ms-marco-MiniLM-L-12-v2-tuned_mediqa-v1 | 166 | null | transformers | 3,858 | Entry not found |
anas/wav2vec2-large-xlsr-arabic | f82ee80d0276f42e4f607efd9d14f452e5756004 | 2021-07-05T19:27:53.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"ar",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | anas | null | anas/wav2vec2-large-xlsr-arabic | 165 | 0 | transformers | 3,859 | ---
language: ar
datasets:
- common_voice: Common Voice Corpus 4
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Hasni XLSR Wav2Vec2 Large 53
results:
- task:
name: Speech Recognition
type: automatic-speech-recognitio... |
ushikado/yuyuyui-chatbot | 0c7304176fef97ebd6a1d547c3323d74d9550df2 | 2021-05-23T13:27:10.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"ja",
"transformers"
] | text-generation | false | ushikado | null | ushikado/yuyuyui-chatbot | 165 | 2 | transformers | 3,860 | ---
language: ja
inference: false
---
# yuyuyui-chatbot
This model is based on [rinna/japanese-gpt2-medium](https://huggingface.co/rinna/japanese-gpt2-medium) and finetuned on Yuyuyui scenario corpus.
## Usage
The model takes a sequence of utterances (context) to generate a subsequent utterance (response). Each utt... |
mlnotes/tape | 2c72f2efa0520efafe6f50edfcc552226bf569cf | 2022-06-01T15:43:03.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | mlnotes | null | mlnotes/tape | 165 | null | transformers | 3,861 | Entry not found |
Felix92/doctr-dummy-torch-crnn-mobilenet-v3-small | dc97c7e0efaa522cebe1badd0de7fffbdec13a22 | 2022-05-25T21:33:45.000Z | [
"pytorch",
"en",
"transformers",
"image-to-text"
] | image-to-text | false | Felix92 | null | Felix92/doctr-dummy-torch-crnn-mobilenet-v3-small | 165 | null | transformers | 3,862 |
---
language: en
pipeline_tag: image-to-text
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/... |
juliensimon/wav2vec2-conformer-rel-pos-large-finetuned-speech-commands | 660e621ec8c4ceea1702da292137b3bf938a4367 | 2022-06-27T21:43:27.000Z | [
"pytorch",
"wav2vec2-conformer",
"audio-classification",
"en",
"dataset:speech_commands",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | audio-classification | false | juliensimon | null | juliensimon/wav2vec2-conformer-rel-pos-large-finetuned-speech-commands | 165 | 1 | transformers | 3,863 | ---
license: apache-2.0
language: en
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec2-conformer-rel-pos-large-finetuned-speech-commands
results:
- task:
type: audio-classification
name: audio classification
dataset:
type: speech_co... |
SushantGautam/SportsSum | 3a4104cd63c9be5577d966f71d101b8f9cd8c707 | 2022-07-23T06:45:09.000Z | [
"pytorch",
"led",
"text2text-generation",
"en",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | SushantGautam | null | SushantGautam/SportsSum | 165 | null | transformers | 3,864 | ---
language:
- en
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: SportsSum
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. -->
# SportsSum
Th... |
BoxCrab/DialoGPT-small-Strider | 554e2d99f54c79bcb61f9cac90eb6eeedf3a84e8 | 2022-07-16T07:50:45.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | BoxCrab | null | BoxCrab/DialoGPT-small-Strider | 165 | null | transformers | 3,865 | ---
tags:
- conversational
---
# Dirk Strider DialoGPT Model |
bhadresh-savani/electra-base-emotion | 1e8c5c4dcdc26c845b56b7ca5c6499f610ea8c8b | 2022-07-14T07:01:38.000Z | [
"pytorch",
"tf",
"jax",
"electra",
"text-classification",
"en",
"dataset:emotion",
"transformers",
"emotion",
"license:apache-2.0",
"model-index"
] | text-classification | false | bhadresh-savani | null | bhadresh-savani/electra-base-emotion | 164 | null | transformers | 3,866 | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- emotion
- pytorch
license: apache-2.0
datasets:
- emotion
metrics:
- Accuracy, F1 Score
model-index:
- name: bhadresh-savani/electra-base-emotion
results:
... |
nlptown/flaubert_small_cased_sentiment | e024d6296b3f800fa6cc165a9b5e4a5adf0dff94 | 2022-05-17T07:43:58.000Z | [
"pytorch",
"tf",
"flaubert",
"text-classification",
"fr",
"dataset:amazon_reviews_multi",
"transformers",
"license:mit"
] | text-classification | false | nlptown | null | nlptown/flaubert_small_cased_sentiment | 164 | 1 | transformers | 3,867 | ---
language:
- fr
datasets:
- amazon_reviews_multi
license: mit
---
# flaubert_small_cased_sentiment
This is a `flaubert_small_cased` model finetuned for sentiment analysis on product reviews in French. It predicts the sentiment of the review, from `very_negative` (1 star) to `very_positive` (5 stars).
This model i... |
asahi417/lmqg-mbart-large-cc25-jaquad | f4eaebfbfa4faca6beafd3c2635f8f0f151dc216 | 2022-06-09T12:16:42.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"ja",
"dataset:asahi417/qg_jaquad",
"transformers",
"question generation",
"license:cc-by-4.0",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-mbart-large-cc25-jaquad | 164 | null | transformers | 3,868 | ---
language: ja
tags:
- question generation
license: cc-by-4.0
datasets:
- asahi417/qg_jaquad
metrics:
- bleu
- meteor
- rouge
- bertscore
widget:
- text: "ゾフィーは貴族出身ではあったが王族出身ではなく、ハプスブルク家の皇位継承者であるフランツ・フェルディナントとの結婚は貴賤結婚となった。皇帝フランツ・ヨーゼフは、2人の間に生まれた子孫が皇位を継がないことを条件として結婚を承認していた。視察が予定されている<hl>6月28日<hl>は2人の14回目の結婚記念日であった。"
... |
jplu/adel-dbpedia-linking | 4187ee10a50fb812a3a798840b21df7b748faddd | 2022-07-22T14:20:54.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | jplu | null | jplu/adel-dbpedia-linking | 164 | null | transformers | 3,869 | Entry not found |
MoritzLaurer/DeBERTa-v3-base-mnli | 3d5861d4fd73bd03dcb8a414558dfb53d2b75188 | 2022-01-15T14:51:04.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"arxiv:2006.03654",
"transformers",
"zero-shot-classification"
] | zero-shot-classification | false | MoritzLaurer | null | MoritzLaurer/DeBERTa-v3-base-mnli | 163 | 2 | transformers | 3,870 | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
metrics:
- accuracy
pipeline_tag: zero-shot-classification
---
# DeBERTa-v3-base-mnli-fever-anli
## Model description
This model was trained on the MultiNLI dataset, which consists of 392 702 NLI hypothesis-premise pairs.
The base model is [De... |
asahi417/lmqg-bart-large-squad | 620ed38a2815c0defdb465331e9af5d39f292f66 | 2022-06-09T18:13:02.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:asahi417/qg_squad",
"transformers",
"question generation",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-bart-large-squad | 163 | null | transformers | 3,871 | ---
language:
- en
tags:
- question generation
license: mit
datasets:
- asahi417/qg_squad
metrics:
- bleu
- meteor
- rouge
- bertscore
- moverscore
widget:
- text: "<hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
example_title... |
gagan3012/keytotext | e72f603ed3cf09dc685c70f7f06465613cf42dad | 2021-03-11T20:23:32.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | gagan3012 | null | gagan3012/keytotext | 163 | null | transformers | 3,872 | # keytotext
Idea is to build a model which will take keywords as inputs and generate sentences as outputs.
### Model:
Two Models have been built:
- Using T5-base size = 850 MB can be found here: https://huggingface.co/gagan3012/keytotext
- Using T5-small size = 230 MB can be found here: https://huggingface.co/gag... |
josmunpen/mt5-small-spanish-summarization | 555ac6380d9199146da607252d2686ca36b4053e | 2021-11-03T09:47:51.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"es",
"dataset:larazonpublico",
"dataset:es",
"transformers",
"summarization",
"spanish",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | josmunpen | null | josmunpen/mt5-small-spanish-summarization | 163 | null | transformers | 3,873 |
---
language:
- es
thumbnail:
tags:
- summarization
- mt5
- spanish
license: apache-2.0
datasets:
- larazonpublico
- es
metrics:
- rouge
widget:
- text: "La Guardia Civil ha desarticulado un grupo organizado dedicado a copiar en los examenes teoricos para la obtencion del permiso de conducir. Para ello, empleaban re... |
loodos/bert-base-turkish-uncased | 7875a51367752147af6ac44b131992284a4543b3 | 2021-05-19T22:04:30.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"tr",
"transformers"
] | null | false | loodos | null | loodos/bert-base-turkish-uncased | 163 | 2 | transformers | 3,874 | ---
language: tr
---
# Turkish Language Models with Huggingface's Transformers
As R&D Team at Loodos, we release cased and uncased versions of most recent language models for Turkish. More details about pretrained models and evaluations on downstream tasks can be found [here (our repo)](https://github.com/Loodos/turk... |
yhavinga/t5-v1.1-base-dutch-cnn-test | 85572934973c29c53fb27037c4280162fbe316ba | 2022-01-19T10:31:39.000Z | [
"pytorch",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"nl",
"dataset:yhavinga/mc4_nl_cleaned",
"dataset:ml6team/cnn_dailymail_nl",
"transformers",
"summarization",
"seq2seq",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | yhavinga | null | yhavinga/t5-v1.1-base-dutch-cnn-test | 163 | 1 | transformers | 3,875 | ---
language:
- nl
datasets:
- yhavinga/mc4_nl_cleaned
- ml6team/cnn_dailymail_nl
tags:
- summarization
- t5
- seq2seq
license: apache-2.0
pipeline_tag: summarization
widget:
- text: "Het Van Goghmuseum in Amsterdam heeft vier kostbare prenten verworven van Mary Cassatt, de Amerikaanse impressionistische kunstenaar en ... |
ixa-ehu/roberta-eus-euscrawl-large-cased | 8762305040656446e41da360b0183d3f9e2f8262 | 2022-03-16T11:49:05.000Z | [
"pytorch",
"roberta",
"fill-mask",
"eu",
"arxiv:2203.08111",
"transformers",
"basque",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | fill-mask | false | ixa-ehu | null | ixa-ehu/roberta-eus-euscrawl-large-cased | 163 | 1 | transformers | 3,876 | ---
language: eu
license: cc-by-nc-4.0
tags:
- basque
- roberta
---
# Roberta-eus Euscrawl large cased
This is a RoBERTa model for Basque model presented in [Does corpus quality really matter for low-resource languages?](https://arxiv.org/abs/2203.08111). There are several models for Basque using the RoBERTa architec... |
Felix92/doctr-dummy-torch-vgg16-bn-r | 760cb447ee57d0fc9cd76c3f5eeb5078d2e60cb5 | 2022-04-14T07:36:36.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-vgg16-bn-r | 163 | null | transformers | 3,877 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
malmarjeh/t5-arabic-text-summarization | fab697056620790cf5f5a4e80e54fe5b6c796d93 | 2022-06-29T14:14:41.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ar",
"transformers",
"Arabic T5",
"T5",
"MSA",
"Arabic Text Summarization",
"Arabic News Title Generation",
"Arabic Paraphrasing",
"autotrain_compatible"
] | text2text-generation | false | malmarjeh | null | malmarjeh/t5-arabic-text-summarization | 163 | null | transformers | 3,878 | ---
language:
- ar
tags:
- Arabic T5
- T5
- MSA
- Arabic Text Summarization
- Arabic News Title Generation
- Arabic Paraphrasing
widget:
- text: "شهدت مدينة طرابلس، مساء أمس الأربعاء، احتجاجات شعبية وأعمال شغب لليوم الثالث على التوالي، وذلك بسبب تردي الوضع المعيشي والاقتصادي. واندلعت مواجهات عنيفة وعملي... |
emilys/twitter-roberta-base-CoNLL | 740b982cf4186376bede6e9629e51ea45a4b6f97 | 2022-07-01T12:13:20.000Z | [
"pytorch",
"roberta",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | emilys | null | emilys/twitter-roberta-base-CoNLL | 163 | null | transformers | 3,879 | ---
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: twitter-roberta-base-CoNLL
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll2003
... |
PrimeQA/squad-v1-xlm-roberta-large | dba97fb0d333fb5cddd8681c65be715448af2b90 | 2022-07-07T20:28:50.000Z | [
"pytorch",
"xlm-roberta",
"multilingual",
"arxiv:1606.05250",
"arxiv:1910.11856",
"arxiv:1911.02116",
"transformers",
"MRC",
"SQuAD 1.1",
"xlm-roberta-large",
"license:apache-2.0"
] | null | false | PrimeQA | null | PrimeQA/squad-v1-xlm-roberta-large | 163 | null | transformers | 3,880 |
---
tags:
- MRC
- SQuAD 1.1
- xlm-roberta-large
language:
- multilingual
license: apache-2.0
---
# Model description
An XLM-RoBERTa reading comprehension model for [SQuAD 1.1](https://aclanthology.org/D16-1264/).
The model is initialized with [xlm-roberta-large](https://huggingface.co/xlm-roberta-large/) and fine-... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi | cc503d0d5753536c644b157852932e825048635e | 2021-10-17T11:05:12.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi | 162 | null | transformers | 3,881 | ---
language:
- ar
license: apache-2.0
widget:
- text: "عامل ايه ؟"
---
# CAMeLBERT-Mix DID NADI Model
## Model description
**CAMeLBERT-Mix DID NADI Model** is a dialect identification (DID) model that was built by fine-tuning the [CAMeLBERT-Mix](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix/) model... |
MutazYoune/Absa_AspectSentiment_hotels | be75f8d59f178f496fde1f16e95e70444d246e41 | 2021-05-18T21:42:54.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | MutazYoune | null | MutazYoune/Absa_AspectSentiment_hotels | 162 | null | transformers | 3,882 | Entry not found |
Narrativa/byt5-base-tweet-hate-detection | f064959ebf565c9a83e6fb6626574c177170186f | 2021-06-30T15:05:08.000Z | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:tweets_hate_speech_detection",
"arxiv:1907.06292",
"arxiv:1910.10683",
"transformers",
"hate",
"speech",
"autotrain_compatible"
] | text2text-generation | false | Narrativa | null | Narrativa/byt5-base-tweet-hate-detection | 162 | 5 | transformers | 3,883 | ---
language: en
datasets:
- tweets_hate_speech_detection
tags:
- hate
- speech
widget:
- text: "@user black lives really matter?"
---
# ByT5-base fine-tuned for Hate Speech Detection (on Tweets)
[ByT5](https://huggingface.co/google/byt5-base) base fine-tuned on [tweets hate speech detection](https://huggingface.co... |
Helsinki-NLP/opus-mt-tc-big-en-el | 26c3999f0b30223bbbbe826c5c89bdf726d7bd71 | 2022-06-01T13:04:21.000Z | [
"pytorch",
"marian",
"text2text-generation",
"el",
"en",
"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-en-el | 162 | null | transformers | 3,884 | ---
language:
- el
- en
tags:
- translation
- opus-mt-tc
license: cc-by-4.0
model-index:
- name: opus-mt-tc-big-en-el
results:
- task:
name: Translation eng-ell
type: translation
args: eng-ell
dataset:
name: flores101-devtest
type: flores_101
args: eng ell devtest
metrics... |
Felix92/doctr-dummy-torch-resnet18 | 1b46de7ced522d5fcfb49c6e6c635c3c26fc5170 | 2022-04-14T07:39:52.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-resnet18 | 162 | null | transformers | 3,885 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-resnet31 | a98d9d54751a725b80d4e88d9ff2bf2a777c1226 | 2022-04-14T07:42:21.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-resnet31 | 162 | null | transformers | 3,886 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-resnet34 | fe7dbf9c393ddee576d03938738bd8408a412ebc | 2022-04-14T07:48:34.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-resnet34 | 162 | null | transformers | 3,887 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-resnet34-wide | 799d196f8b345784140cdb4f95893a2e92f8c753 | 2022-04-14T07:51:35.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-resnet34-wide | 162 | null | transformers | 3,888 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-resnet50 | af9ab31ad823a7dd8a942778eb752cdc1dedee45 | 2022-04-14T08:06:25.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-resnet50 | 162 | null | transformers | 3,889 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: classification
https://github.com/mindee/doctr
### Example... |
Felix92/doctr-dummy-torch-db-resnet50-rotation | 1dfc54b8c142f21337bae1ad0396e093c9639399 | 2022-04-14T08:59:04.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-db-resnet50-rotation | 162 | null | transformers | 3,890 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
Felix92/doctr-dummy-torch-linknet-resnet18 | c1c72e4ad92e29a79ced012722e2f05ff535a680 | 2022-04-14T09:02:14.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-linknet-resnet18 | 162 | null | transformers | 3,891 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
Felix92/doctr-dummy-torch-linknet-resnet34 | 9c16f162f7b750fd4683a557eed8132667041bff | 2022-04-14T09:17:24.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-linknet-resnet34 | 162 | null | transformers | 3,892 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
Felix92/doctr-dummy-torch-linknet-resnet50 | c3017c9a02a74620ac54204bfc8548a0f05eb58d | 2022-04-14T09:20:06.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-linknet-resnet50 | 162 | null | transformers | 3,893 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: detection
https://github.com/mindee/doctr
### Example usag... |
Felix92/doctr-dummy-torch-crnn-mobilenet-v3-large | 949a3f701b962e09650fceea80e974d9c39b1f3f | 2022-04-14T09:27:19.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-crnn-mobilenet-v3-large | 162 | null | transformers | 3,894 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/mindee/doctr
### Example us... |
Felix92/doctr-dummy-torch-fasterrcnn-mobilenet-v3-large-fpn | 7b14a117cd512cf28ebe92dbd53ce632117b4918 | 2022-04-14T09:28:24.000Z | [
"pytorch",
"en",
"transformers"
] | null | false | Felix92 | null | Felix92/doctr-dummy-torch-fasterrcnn-mobilenet-v3-large-fpn | 162 | null | transformers | 3,895 |
---
language: en
---
<p align="center">
<img src="https://github.com/mindee/doctr/releases/download/v0.3.1/Logo_doctr.gif" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: obj_detection
https://github.com/mindee/doctr
### Example ... |
dbmdz/bert-base-german-europeana-td-cased | 4385d7ebbbfa13baec7db3cc2cf9415944e607cd | 2022-04-29T13:29:25.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/bert-base-german-europeana-td-cased | 162 | null | transformers | 3,896 | ---
license: mit
---
|
adamlin/distilbert-base-cased-sgd_qa-step5000 | 593404c329812d8283e5dba10df64fabc4da9d60 | 2021-02-09T15:02:35.000Z | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | adamlin | null | adamlin/distilbert-base-cased-sgd_qa-step5000 | 161 | null | transformers | 3,897 | Entry not found |
asahi417/lmqg-t5-large-squad | 4c5c2f87963e691d076b61274fa7773efd0570cb | 2022-06-09T22:43:17.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:asahi417/qg_squad",
"transformers",
"question generation",
"license:cc-by-4.0",
"autotrain_compatible"
] | text2text-generation | false | asahi417 | null | asahi417/lmqg-t5-large-squad | 161 | 1 | transformers | 3,898 | ---
language: en
tags:
- question generation
license: cc-by-4.0
datasets:
- asahi417/qg_squad
metrics:
- bleu
- meteor
- rouge
- bertscore
- moverscore
widget:
- text: "generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Recor... |
cambridgeltl/trans-encoder-cross-simcse-bert-large | 893fab51dfd0e8da9ecd523aa856dc71af91b88a | 2021-11-26T18:28:18.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | cambridgeltl | null | cambridgeltl/trans-encoder-cross-simcse-bert-large | 161 | null | transformers | 3,899 | Entry not found |
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