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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
lazyturtl/roomclassifier | 9459b019773ca1279fe099c515762acf5e06b71e | 2022-03-31T01:09:57.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | lazyturtl | null | lazyturtl/roomclassifier | 73 | null | transformers | 5,300 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: roomclassifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9402984976768494
---
# roomclassifier
Au... |
Nonem100/Test-Model | 57666cfe40a32679221ada968a18cbffb8254b64 | 2022-03-31T15:19:38.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Nonem100 | null | Nonem100/Test-Model | 73 | null | transformers | 5,301 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: Test-Model
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9017857313156128
---
# Test-Model
Autogenera... |
nickmuchi/swin-tiny-patch4-window7-224-finetuned-eurosat | 55f500ccbd1ee1c7878e51ff889faf0a0327c708 | 2022-05-24T02:08:03.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"dataset:nielsr/eurosat-demo",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | nickmuchi | null | nickmuchi/swin-tiny-patch4-window7-224-finetuned-eurosat | 73 | null | transformers | 5,302 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
- nielsr/eurosat-demo
widget:
- src: https://drive.google.com/uc?id=1trKgvkMRQ3BB0VcqnDwmieLxXhWmS8rq
example_title: Annual Crop
- src: https://drive.google.com/uc?id=1kWQbPNHVa_JscS0age5E0UOSBcU1bh18
example_title: Forest
- src: https:... |
KoichiYasuoka/deberta-base-japanese-luw-upos | 7cbf54c18a6139d57cb47b0bc2e97bf87a9c3191 | 2022-07-23T14:43:41.000Z | [
"pytorch",
"deberta-v2",
"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/deberta-base-japanese-luw-upos | 73 | null | transformers | 5,303 | ---
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。"
---
# deberta-base-japanese-luw-upos
## Model Description
This is a DeBERTa(V2) mod... |
roydcarlson/grain | 36e78c0a9507f36b58a71e2f9f5c859af2d9537f | 2022-05-27T17:01:52.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | roydcarlson | null | roydcarlson/grain | 73 | null | transformers | 5,304 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: grain
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.6607142686843872
---
# grain
Autogenerated by Hug... |
KL/swin-tiny-patch4-window7-224-finetuned-eurosat | ccbaa5f4cf45f5d4ee5eac3950bca6a8c293faf1 | 2022-05-29T12:07:22.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"transformers"
] | image-classification | false | KL | null | KL/swin-tiny-patch4-window7-224-finetuned-eurosat | 73 | null | transformers | 5,305 | Entry not found |
RUCAIBox/mtl-data-to-text | ed44b68242f30903d42abf0f13c1d9af5c1bb8f8 | 2022-06-27T02:27:10.000Z | [
"pytorch",
"mvp",
"en",
"arxiv:2206.12131",
"transformers",
"text-generation",
"text2text-generation",
"license:apache-2.0"
] | text2text-generation | false | RUCAIBox | null | RUCAIBox/mtl-data-to-text | 73 | null | transformers | 5,306 | ---
license: apache-2.0
language:
- en
tags:
- text-generation
- text2text-generation
pipeline_tag: text2text-generation
widget:
- text: "Describe the following data: Iron Man | instance of | Superhero [SEP] Stan Lee | creator | Iron Man"
example_title: "Example1"
- text: "Describe the following data: First Clearing ... |
aws-ai/dse-bert-base | 918ad931256ade24add8b1840a710e9e96bc9b40 | 2022-07-10T19:43:15.000Z | [
"pytorch",
"bert",
"transformers"
] | null | false | aws-ai | null | aws-ai/dse-bert-base | 73 | null | transformers | 5,307 | Entry not found |
CLTL/gm-ner-xlmrbase | 120252d7c808f3997ca6423a57087077273f79e0 | 2021-11-09T16:14:39.000Z | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"nl",
"transformers",
"dighum",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | CLTL | null | CLTL/gm-ner-xlmrbase | 72 | null | transformers | 5,308 | ---
language: nl
license: apache-2.0
tags:
- dighum
pipeline_tag: token-classification
---
# Early-modern Dutch NER (General Letters)
## Description
This is a fine-tuned NER model for early-modern Dutch United East India Company (VOC) letters based on XLM-R_base [(Conneau et al., 2020)](https://aclanthology.org/2020.... |
Helsinki-NLP/opus-mt-aav-en | f0d56d0d1bb26a58faa0a70d8804809a58e6a06d | 2021-01-18T07:45:52.000Z | [
"pytorch",
"marian",
"text2text-generation",
"vi",
"km",
"aav",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-aav-en | 72 | null | transformers | 5,309 | ---
language:
- vi
- km
- aav
- en
tags:
- translation
license: apache-2.0
---
### aav-eng
* source group: Austro-Asiatic languages
* target group: English
* OPUS readme: [aav-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/aav-eng/README.md)
* model: transformer
* source language(s)... |
Helsinki-NLP/opus-mt-it-vi | 043beee1bbe972313387181b4fd1d4796a15fe0a | 2020-08-21T14:42:46.000Z | [
"pytorch",
"marian",
"text2text-generation",
"it",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-it-vi | 72 | null | transformers | 5,310 | ---
language:
- it
- vi
tags:
- translation
license: apache-2.0
---
### ita-vie
* source group: Italian
* target group: Vietnamese
* OPUS readme: [ita-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ita-vie/README.md)
* model: transformer-align
* source language(s): ita
* target lang... |
Helsinki-NLP/opus-mt-ru-vi | 5fc954aae39caa5f6f65dc8837328254d4927b07 | 2020-08-21T14:42:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ru",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ru-vi | 72 | null | transformers | 5,311 | ---
language:
- ru
- vi
tags:
- translation
license: apache-2.0
---
### rus-vie
* source group: Russian
* target group: Vietnamese
* OPUS readme: [rus-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/rus-vie/README.md)
* model: transformer-align
* source language(s): rus
* target lang... |
Helsinki-NLP/opus-mt-vi-de | 5732a1f19967c1ba48e9ac85428f4e6cfea6ecc3 | 2020-08-21T14:42:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"vi",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-vi-de | 72 | null | transformers | 5,312 | ---
language:
- vi
- de
tags:
- translation
license: apache-2.0
---
### vie-deu
* source group: Vietnamese
* target group: German
* OPUS readme: [vie-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/vie-deu/README.md)
* model: transformer-align
* source language(s): vie
* target langu... |
Maltehb/danish-bert-botxo-ner-dane | 0535804050650a7c1dde9b51af68b1e039d6df0a | 2021-11-12T08:36:46.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"token-classification",
"da",
"dataset:common_crawl",
"dataset:wikipedia",
"dataset:dindebat.dk",
"dataset:hestenettet.dk",
"dataset:danish OpenSubtitles",
"transformers",
"danish",
"masked-lm",
"botxo",
"license:cc-by-4.0",
"autotrain_compatible"
] | token-classification | false | Maltehb | null | Maltehb/danish-bert-botxo-ner-dane | 72 | 1 | transformers | 5,313 | ---
language: da
tags:
- danish
- bert
- masked-lm
- botxo
license: cc-by-4.0
datasets:
- common_crawl
- wikipedia
- dindebat.dk
- hestenettet.dk
- danish OpenSubtitles
widget:
- text: "Chili Jensen, som bor på Danmarksgade 12, køber chilifrugter fra Netto."
---
# Danish BERT (version 2, uncased) by [Certainly](https:... |
Muennighoff/SGPT-1.3B-weightedmean-nli-bitfit | 21ac01bac24bf051aa64428d105d95921ec4e562 | 2022-06-18T13:04:47.000Z | [
"pytorch",
"gpt_neo",
"feature-extraction",
"arxiv:2202.08904",
"sentence-transformers",
"sentence-similarity"
] | sentence-similarity | false | Muennighoff | null | Muennighoff/SGPT-1.3B-weightedmean-nli-bitfit | 72 | null | sentence-transformers | 5,314 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# SGPT-1.3B-weightedmean-nli-bitfit
## Usage
For usage instructions, refer to our codebase: https://github.com/Muennighoff/sgpt
## Evaluation Results
For eval results, refer to the eval folder or our... |
Rostlab/prot_t5_xxl_bfd | 34a420890330b9335d7292c36d8950c7952f09c9 | 2020-12-11T10:20:10.000Z | [
"pytorch",
"t5",
"feature-extraction",
"transformers"
] | feature-extraction | false | Rostlab | null | Rostlab/prot_t5_xxl_bfd | 72 | null | transformers | 5,315 | Entry not found |
aloxatel/mbert | cce439353fe629e6fdb88d10cb326d0a7a405a02 | 2021-05-19T11:43:34.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | aloxatel | null | aloxatel/mbert | 72 | 1 | transformers | 5,316 | Entry not found |
cambridgeltl/tacl-bert-base-chinese | c86daf0753de79319b2066897a54c6cae64daf85 | 2021-10-28T17:51:55.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | cambridgeltl | null | cambridgeltl/tacl-bert-base-chinese | 72 | null | transformers | 5,317 | Entry not found |
jpcorb20/toxic-detector-distilroberta | 88d1b244e128ed29bc23a68338258784cf2e4008 | 2021-05-20T17:25:58.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | jpcorb20 | null | jpcorb20/toxic-detector-distilroberta | 72 | 1 | transformers | 5,318 | # Distilroberta for toxic comment detection
See my GitHub repo [toxic-comment-server](https://github.com/jpcorb20/toxic-comment-server)
The model was trained from [DistilRoberta](https://huggingface.co/distilroberta-base) on [Kaggle Toxic Comments](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challeng... |
mrm8488/distilbert-base-multi-cased-finetuned-typo-detection | 3d191639cca2821fbfebef7c779a2bba6228a6bb | 2020-12-11T21:53:44.000Z | [
"pytorch",
"distilbert",
"token-classification",
"multilingual",
"transformers",
"autotrain_compatible"
] | token-classification | false | mrm8488 | null | mrm8488/distilbert-base-multi-cased-finetuned-typo-detection | 72 | null | transformers | 5,319 | ---
language: multilingual
thumbnail:
---
# DISTILBERT 🌎 + Typo Detection ✍❌✍✔
[distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) fine-tuned on [GitHub Typo Corpus](https://github.com/mhagiwara/github-typo-corpus) for **typo detection** (using *NER* style)
## Details of ... |
nateraw/rare-puppers-09-04-2021 | 55954fde8839b77f629c664ef2a9626181f2796b | 2021-09-04T20:46:06.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nateraw | null | nateraw/rare-puppers-09-04-2021 | 72 | null | transformers | 5,320 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers-09-04-2021
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8657407164573669
---
# rare-puppe... |
saburbutt/roberta_base_tweetqa_model | 433145b954f69bff58a02725757f9f1f33b50e06 | 2021-05-20T19:58:30.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | saburbutt | null | saburbutt/roberta_base_tweetqa_model | 72 | null | transformers | 5,321 | Entry not found |
stevenshoemaker/horror | de0fda6abd5856125fe2c236c8ca7cb1b58c0fcc | 2021-05-23T12:56:03.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | stevenshoemaker | null | stevenshoemaker/horror | 72 | null | transformers | 5,322 | Entry not found |
facebook/wav2vec2-base-es-voxpopuli-v2 | b982ca9b90f554145513d3a5e524f65bb6f20be0 | 2022-02-27T13:11:53.000Z | [
"pytorch",
"wav2vec2",
"pretraining",
"es",
"dataset:voxpopuli",
"arxiv:2101.00390",
"transformers",
"audio",
"automatic-speech-recognition",
"voxpopuli-v2",
"license:cc-by-nc-4.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-base-es-voxpopuli-v2 | 72 | null | transformers | 5,323 | ---
language: es
tags:
- audio
- automatic-speech-recognition
- voxpopuli-v2
datasets:
- voxpopuli
license: cc-by-nc-4.0
inference: false
---
# Wav2Vec2-base-VoxPopuli-V2
[Facebook's Wav2Vec2](https://ai.facebook.com/blog/wav2vec-20-learning-the-structure-of-speech-from-raw-audio/) base model pretrained only in **es*... |
nickmuchi/vit-finetuned-cats-dogs | 5cefa517e61aa63ca6b1642d887c3a65b233ef34 | 2022-03-01T13:15:13.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nickmuchi | null | nickmuchi/vit-finetuned-cats-dogs | 72 | null | transformers | 5,324 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
widget:
- src: https://cdn.pixabay.com/photo/2021/09/19/12/19/animal-6637774_1280.jpg
example_title: Dog
- src: https://cdn.pixabay.com/photo/2017/02/20/18/03/cat-2083492_1280.jpg
example_title: Cat
model-index:
- name: vit-finetuned-cats... |
hafidber/fruits | 28be4b5394f7cdaf3b8018e7f93e10552dbe7a27 | 2022-04-07T15:02:57.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | hafidber | null | hafidber/fruits | 72 | null | transformers | 5,325 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: fruits
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9910714030265808
---
# fruits
Autogenerated by H... |
nielsr/swin-tiny-patch4-window7-224-finetuned-cifar10 | b21db45e5b3fbd1e83f9787e07f3fe80ad254206 | 2022-04-11T12:19:54.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | nielsr | null | nielsr/swin-tiny-patch4-window7-224-finetuned-cifar10 | 72 | null | transformers | 5,326 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-cifar10
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
... |
Zayn/VIT_Basic | d8ecb81a9b939600d0e850c6e3c160c7a14cc37e | 2022-04-22T16:19:34.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Zayn | null | Zayn/VIT_Basic | 72 | null | transformers | 5,327 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: VIT_Basic
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9107142686843872
---
# VIT_Basic
Autogenerate... |
Gunulhona/tbstmodel_v3 | 488b4153082302af6fc4a20d151ce031b80e3dfb | 2022-07-30T08:34:28.000Z | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | Gunulhona | null | Gunulhona/tbstmodel_v3 | 72 | null | transformers | 5,328 | Entry not found |
mrm8488/data2vec-base-finetuned-imagenet1k | 3bfe19761dfeb217806b7302baa7355f7e538f0f | 2022-05-04T14:55:41.000Z | [
"pytorch",
"data2vec-vision",
"image-classification",
"transformers"
] | image-classification | false | mrm8488 | null | mrm8488/data2vec-base-finetuned-imagenet1k | 72 | null | transformers | 5,329 | Entry not found |
Ahmed9275/ALL-test | a6697d6f66bd8c8800fc580debdb85fe93439819 | 2022-05-05T23:55:05.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Ahmed9275 | null | Ahmed9275/ALL-test | 72 | null | transformers | 5,330 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: ALL-test
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9572474360466003
---
# ALL-test
Autogenerated ... |
zzzzzzttt/vit-base-patch16-224-finetuned-eurosat | d1af73b119967cf26591363e14753b10d1b5718a | 2022-05-06T05:29:18.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | zzzzzzttt | null | zzzzzzttt/vit-base-patch16-224-finetuned-eurosat | 72 | null | transformers | 5,331 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args... |
karthiksv/vit-base-beans | da7e199b23fe32e5145d756571e762c1a50d603f | 2022-05-12T15:21:37.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:beans",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | karthiksv | null | karthiksv/vit-base-beans | 72 | null | transformers | 5,332 | ---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- beans
model-index:
- name: vit-base-beans
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 ... |
KoichiYasuoka/deberta-base-japanese-aozora | 4cfed2b76e0089667aec79fb4fce318939282cc8 | 2022-07-23T14:43:28.000Z | [
"pytorch",
"deberta-v2",
"fill-mask",
"ja",
"transformers",
"japanese",
"masked-lm",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | KoichiYasuoka | null | KoichiYasuoka/deberta-base-japanese-aozora | 72 | null | transformers | 5,333 | ---
language:
- "ja"
tags:
- "japanese"
- "masked-lm"
license: "cc-by-sa-4.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
widget:
- text: "日本に着いたら[MASK]を訪ねなさい。"
---
# deberta-base-japanese-aozora
## Model Description
This is a DeBERTa(V2) model pre-trained on 青空文庫 texts. You can fine-tune `deberta-base-japanese-a... |
Annabelleabbott/swin-tiny-patch4-window7-224-finetuned-eurosat | b854e399d64a2351130b6814af6755313f787a0c | 2022-05-25T15:56:42.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | Annabelleabbott | null | Annabelleabbott/swin-tiny-patch4-window7-224-finetuned-eurosat | 72 | null | transformers | 5,334 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
... |
GRANTHE2761/swin-tiny-patch4-window7-224-finetuned-eurosat | b37ddc121c456f71672a41cc430af49eee88e966 | 2022-05-26T09:00:52.000Z | [
"pytorch",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | GRANTHE2761 | null | GRANTHE2761/swin-tiny-patch4-window7-224-finetuned-eurosat | 72 | null | transformers | 5,335 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
... |
Anjoe/kant-gpt2-large | 2e4fda374a8d2bc2b113310efaf19a77d9d65461 | 2022-07-21T14:32:36.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index"
] | text-generation | false | Anjoe | null | Anjoe/kant-gpt2-large | 72 | null | transformers | 5,336 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: kant-gpt2-large
results: []
---
# kant-gpt2-large
This model is a fine-tuned version of [benjamin/gerpt2-large](https://huggingface.co/benjamin/gerpt2-large). It was trained on the "Akademie Ausgabe" of the works of Immanuel Kant.
It achieves the... |
s3h/arabic-token-ged-arabert | 6407a502bd65f8564c68094fe62613db195fa1c7 | 2022-07-01T15:04:33.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | s3h | null | s3h/arabic-token-ged-arabert | 72 | null | transformers | 5,337 | Entry not found |
brjezierski/bert-to-gpt2-german-to-easy-german | 39fd188fbf78a8b3531f47a210f95557c82d8e87 | 2022-07-13T22:47:58.000Z | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | brjezierski | null | brjezierski/bert-to-gpt2-german-to-easy-german | 72 | null | transformers | 5,338 | Entry not found |
DTAI-KULeuven/robbertje-1-gb-bort | 8a8832a3545206b8efb64db369f15d06f4eff0ac | 2022-02-24T09:57:08.000Z | [
"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-bort | 71 | null | transformers | 5,339 | ---
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... |
Geotrend/distilbert-base-ur-cased | 2d74a893b996945026a25aa41ac3a4427b5341b2 | 2021-08-16T13:24:21.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"ur",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/distilbert-base-ur-cased | 71 | null | transformers | 5,340 | ---
language: ur
datasets: wikipedia
license: apache-2.0
---
# distilbert-base-ur-cased
We are sharing smaller versions of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) that handle a custom number of languages.
Our versions give exactly the same representations pro... |
Helsinki-NLP/opus-mt-et-de | d3e6e2fd83bc8b61639fc47ab249dfdd5d981050 | 2021-09-09T21:45:57.000Z | [
"pytorch",
"marian",
"text2text-generation",
"et",
"de",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-et-de | 71 | null | transformers | 5,341 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-et-de
* source languages: et
* target languages: de
* OPUS readme: [et-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/et-de/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-zh-nl | 51af542ab7955009cb30a4759a7bdd9db6a31f9d | 2020-08-21T14:42:52.000Z | [
"pytorch",
"marian",
"text2text-generation",
"zh",
"nl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-zh-nl | 71 | null | transformers | 5,342 | ---
language:
- zh
- nl
tags:
- translation
license: apache-2.0
---
### zho-nld
* source group: Chinese
* target group: Dutch
* OPUS readme: [zho-nld](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-nld/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hani ... |
Lowin/chinese-bigbird-wwm-base-4096 | 5a7324c571df27341d5fdf571d2a4b6a6470d1c2 | 2021-11-24T15:58:17.000Z | [
"pytorch",
"big_bird",
"fill-mask",
"zh",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Lowin | null | Lowin/chinese-bigbird-wwm-base-4096 | 71 | 1 | transformers | 5,343 | ---
language:
- zh
license:
- apache-2.0
---
```python
from transformers import BertTokenizer
from transformers import BigBirdModel
model = BigBirdModel.from_pretrained('Lowin/chinese-bigbird-wwm-base-4096')
tokenizer = BertTokenizer.from_pretrained('Lowin/chinese-bigbird-wwm-base-4096')
```
https://github.com/LowinLi... |
Rolv-Arild/xls-r-300m-npsc-seq2seq | 6d3acfc42af6a610f154a8dfe36050c9b0fd93bb | 2022-02-18T18:51:44.000Z | [
"pytorch",
"tensorboard",
"speech-encoder-decoder",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | Rolv-Arild | null | Rolv-Arild/xls-r-300m-npsc-seq2seq | 71 | null | transformers | 5,344 | ---
tags:
- generated_from_trainer
model-index:
- name: ''
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
#
This model was trained from scratch on the None da... |
SEBIS/code_trans_t5_base_commit_generation | 1a568af651d14ea287897f8507cfbfb65959f39b | 2021-06-23T04:56:59.000Z | [
"pytorch",
"jax",
"t5",
"feature-extraction",
"transformers",
"summarization"
] | summarization | false | SEBIS | null | SEBIS/code_trans_t5_base_commit_generation | 71 | null | transformers | 5,345 | ---
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 base model architecture. It was firs... |
abhilash1910/french-roberta | 2358f6784bcec544c1b00598c8fc8631036384c3 | 2021-09-14T07:17:21.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"fr",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | abhilash1910 | null | abhilash1910/french-roberta | 71 | null | transformers | 5,346 | # Roberta Trained Model For Masked Language Model On French Corpus :robot:
This is a Masked Language Model trained with [Roberta](https://huggingface.co/transformers/model_doc/roberta.html) on a small French News Corpus(Leipzig corpora).
The model is built using Huggingface transformers.
The model can be found at :[F... |
abhiramtirumala/DialoGPT-sarcastic | 796ca7306a806583428e40747632577e5db932bc | 2021-06-30T19:52:43.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | abhiramtirumala | null | abhiramtirumala/DialoGPT-sarcastic | 71 | 4 | transformers | 5,347 |
---
pipeline_tag: conversational
---
This model is a fine-tuned version of Microsoft/DialoGPT-medium trained to created sarcastic responses from the dataset "Sarcasm on Reddit" located [here](https://www.kaggle.com/danofer/sarcasm). |
abinayam/gpt-2-tamil | 752d5c1069d9ae7b43019bd280300950f599c7e8 | 2021-07-23T06:24:40.000Z | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"ta",
"dataset:oscar",
"dataset:IndicNLP",
"transformers"
] | text-generation | false | abinayam | null | abinayam/gpt-2-tamil | 71 | 2 | transformers | 5,348 | ---
language: ta
datasets:
- oscar
- IndicNLP
widget:
- text: 'ஒரு ஊரிலே ஒரு காக்கைக்கு'
---
# GPT2-Tamil
This repository is created as part of the Flax/Jax community week by Huggingface. The aim of this project is to pretrain a language model using GPT-2 specifically for Tamil language.
## Setup:
To setup the pro... |
airesearch/wangchanberta-base-wiki-newmm | 840fd2896fd1a23f9f6366ab458863bdc4e921f8 | 2021-09-11T09:39:18.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"th",
"arxiv:1907.11692",
"arxiv:2101.09635",
"transformers",
"autotrain_compatible"
] | fill-mask | false | airesearch | null | airesearch/wangchanberta-base-wiki-newmm | 71 | null | transformers | 5,349 | ---
language: th
---
# WangchanBERTa base model: `wangchanberta-base-wiki-newmm`
<br>
Pretrained RoBERTa BASE model on Thai Wikipedia corpus.
The script and documentation can be found at [this reposiryory](https://github.com/vistec-AI/thai2transformers).
<br>
## Model description
<br>
The architecture of the pret... |
davanstrien/iiif_manuscript_vit | 37b1ed562376f16bb2dce761dcfd57fc582ba047 | 2022-02-10T22:49:42.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | davanstrien | null | davanstrien/iiif_manuscript_vit | 71 | null | transformers | 5,350 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: iiif_manuscript_vit
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. -->
# i... |
dvm1983/TinyBERT_General_4L_312D_de | 3b3084a67cb7894f26fbc0232ce3e8fbc1b61fc9 | 2021-08-22T16:44:48.000Z | [
"pytorch",
"bert",
"de",
"dataset:wiki",
"arxiv:1909.10351",
"transformers",
"tinybert",
"fill-mask"
] | fill-mask | false | dvm1983 | null | dvm1983/TinyBERT_General_4L_312D_de | 71 | null | transformers | 5,351 | ---
language:
- de
tags:
- tinybert
- fill-mask
datasets:
- wiki
---
Here is represented tinybert model for German language (de). The model was created by distilling of bert base cased model(https://huggingface.co/dbmdz/bert-base-german-cased) in the way described in https://arxiv.org/abs/1909.10351 (TinyBERT: Distil... |
godiec/diam | a83df7f3dc0379b2f64317b1dc0c757a40018053 | 2021-12-13T19:12:32.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | godiec | null | godiec/diam | 71 | null | transformers | 5,352 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: diam
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9775280952453613
---
# diam
Autogenerated by Huggi... |
harr/distilbert-base-uncased-finetuned-ingredients | 4d043103a8ee532364bf569c53e4a06c2eb6d5c5 | 2021-09-11T09:20:35.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"token-classification",
"dataset:ingredients_yes_no",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | harr | null | harr/distilbert-base-uncased-finetuned-ingredients | 71 | 3 | transformers | 5,353 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ingredients_yes_no
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ingredients
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ingredien... |
ml6team/gpt2-medium-dutch-finetune-oscar | 7ae5ea65cb2d434d07da0f3628c0738d8ee5fef5 | 2021-05-23T09:42:53.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"nl",
"transformers",
"adaption",
"recycled",
"gpt2-medium"
] | text-generation | false | ml6team | null | ml6team/gpt2-medium-dutch-finetune-oscar | 71 | 6 | transformers | 5,354 | ---
language: nl
widget:
- text: "De regering heeft beslist dat"
tags:
- adaption
- recycled
- gpt2-medium
- gpt2
pipeline_tag: text-generation
---
# Dutch finetuned GPT2 |
nateraw/baseball-stadium-foods | 1252d68fce7e2a3e3855b43439992beccea3f716 | 2021-06-30T07:11:21.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nateraw | null | nateraw/baseball-stadium-foods | 71 | null | transformers | 5,355 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: baseball-stadium-foods
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9107142686843872
---
# baseball-st... |
nateraw/donut-or-bagel | 408739a81234d039cbead3c0f956ef1f729a4739 | 2021-07-10T19:54:49.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nateraw | null | nateraw/donut-or-bagel | 71 | null | transformers | 5,356 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: donut-or-bagel
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9375
---
# donut-or-bagel
Autogenerated ... |
nateraw/planes-trains-automobiles | dcf495d94e1cb0e9e7fb6bf8ac3c05c74dc3c8df | 2021-08-23T21:42:21.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"generated_from_trainer",
"license:apache-2.0"
] | image-classification | false | nateraw | null | nateraw/planes-trains-automobiles | 71 | null | transformers | 5,357 | ---
license: apache-2.0
tags:
- huggingpics
- image-classification
- generated_from_trainer
metrics:
- accuracy
model_index:
- name: planes-trains-automobiles
results:
- task:
name: Image Classification
type: image-classification
metric:
name: Accuracy
type: accuracy
value: 0.98507... |
sonoisa/vl-t5-base-japanese | d5d3c72dcbad8ebb55e51ffe7ede7ba786edb5cd | 2021-10-04T11:13:35.000Z | [
"pytorch",
"t5",
"ja",
"dataset:wikipedia",
"dataset:oscar",
"dataset:cc100",
"dataset:ms_coco",
"dataset:visual_genome",
"dataset:coco_captions",
"dataset:vqa",
"dataset:gqa",
"arxiv:2102.02779",
"transformers",
"vl-t5",
"license:cc-by-sa-4.0"
] | null | false | sonoisa | null | sonoisa/vl-t5-base-japanese | 71 | null | transformers | 5,358 | ---
language: ja
tags:
- vl-t5
license: cc-by-sa-4.0
datasets:
- wikipedia
- oscar
- cc100
- ms_coco
- visual_genome
- coco_captions
- vqa
- gqa
---
# 日本語VL-T5事前学習済みモデル
This is a VL-T5 (Unifying Vision-and-Language Tasks via Text Generation) model pretrained on Japanese corpus.
日本語コーパスを用いて事前学習を行ったVL-T5 (Unifying Vis... |
suhnylla/planes_airlines | 31689e3a1c78ffce0aebfa030bfa00c28a8eafc8 | 2021-07-22T02:21:24.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | suhnylla | null | suhnylla/planes_airlines | 71 | null | transformers | 5,359 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: planes_airlines
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.32307693362236023
---
# planes_airlines
... |
hf-internal-testing/tiny-plbart | 4744258777b2b19aab82ccab91cc4904b1f305a9 | 2022-04-05T14:38:10.000Z | [
"pytorch",
"plbart",
"text-classification",
"transformers"
] | text-classification | false | hf-internal-testing | null | hf-internal-testing/tiny-plbart | 71 | null | transformers | 5,360 | Entry not found |
shniranjan/wav2vec2-large-xlsr-300m-nepali | f95476bd5f3981d3684da3245b32334865c1550a | 2022-04-15T02:29:21.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ne",
"transformers",
"speech-to-text"
] | automatic-speech-recognition | false | shniranjan | null | shniranjan/wav2vec2-large-xlsr-300m-nepali | 71 | null | transformers | 5,361 | ## Usage
The model can be used directly (without a language model) as follows:
---
language:
- ne
tags:
- speech-to-text
---
```python
import soundfile as sf
import torch
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import argparse
def parse_transcription(wav_file):
# load pretrained model
process... |
zzzzzzttt/swin-tiny-patch4-window7-224-finetuned-eurosat | d6d2e6689168ae3466defaaf0020a46b334d76d8 | 2022-04-14T12:20:10.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | zzzzzzttt | null | zzzzzzttt/swin-tiny-patch4-window7-224-finetuned-eurosat | 71 | null | transformers | 5,362 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
... |
mirbostani/bert-base-uncased-finetuned-newsqa | 4b47302119d59350e95a2f5c6d4aee61dde202e8 | 2022-04-25T21:01:37.000Z | [
"pytorch",
"bert",
"question-answering",
"en",
"dataset:newsqa",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | false | mirbostani | null | mirbostani/bert-base-uncased-finetuned-newsqa | 71 | null | transformers | 5,363 | ---
language:
- en
tags:
- question-answering
license: apache-2.0
datasets:
- newsqa
metrics:
- f1
- exact_match
---
# BERT Base Uncased Finetuned on NewsQA
Examples with `noAnswer` and `badQuestion` are not included in the training process.
```shell
$ cd ~/projects/transformers/examples/legacy/question-answering
$... |
beomi/KcELECTRA-small-v2022 | d4f840c28ae2cc26b7639c7ced8ffa61169f4607 | 2022-04-27T05:48:25.000Z | [
"pytorch",
"electra",
"pretraining",
"transformers",
"license:mit"
] | null | false | beomi | null | beomi/KcELECTRA-small-v2022 | 71 | 2 | transformers | 5,364 | ---
license: mit
---
|
mbyanfei/swin-tiny-patch4-window7-224-finetuned-eurosat | f7868f313d240691001ebd43dce8f831a64283e1 | 2022-05-27T18:43:27.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | mbyanfei | null | mbyanfei/swin-tiny-patch4-window7-224-finetuned-eurosat | 71 | null | transformers | 5,365 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
... |
fxtentacle/wav2vec2-xls-r-1b-tevr | 7accec19468fc64f5ea54c11d8bab80342bc29f3 | 2022-06-28T16:22:18.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"de",
"dataset:common_voice",
"arxiv:2206.12693",
"transformers",
"audio",
"speech",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | fxtentacle | null | fxtentacle/wav2vec2-xls-r-1b-tevr | 71 | 4 | transformers | 5,366 | ---
language: de
datasets:
- common_voice
inference: false
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- hf-asr-leaderboard
license: apache-2.0
model-index:
- name: wav2vec 2.0 XLS-R 1B + TEVR tokens + 5-gram LM by Hajo Nils Krabbenhöft
results:
- task:
name: Speech Recognition... |
Jihuai/bert-ancient-chinese | fd2d21041bf427d78405f6f9320478fae7710b54 | 2022-06-09T11:53:34.000Z | [
"pytorch",
"bert",
"fill-mask",
"zh",
"transformers",
"chinese",
"classical chinese",
"literary chinese",
"ancient chinese",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Jihuai | null | Jihuai/bert-ancient-chinese | 71 | 0 | transformers | 5,367 | ---
language:
- "zh"
tags:
- "chinese"
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "bert"
- "pytorch"
inference: false
license: "apache-2.0"
---
# bert-ancient-chinese
## Introduction
With the current wave of Artificial Intelligence and Digital Humanities sweeping the world, the automat... |
lindsayng/t5-base-base-sweep-b3acbf3b | ce971bbd3cd1ab4818a0c1c8bc04ed0fcdf04ff8 | 2022-06-13T14:19:26.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | lindsayng | null | lindsayng/t5-base-base-sweep-b3acbf3b | 71 | null | transformers | 5,368 | Entry not found |
ArnavL/roberta-base-imdb-0 | 887f1f8080ca67925d43c3d81c132ef834bdd2d5 | 2022-07-11T10:46:26.000Z | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | ArnavL | null | ArnavL/roberta-base-imdb-0 | 71 | null | transformers | 5,369 | Entry not found |
ARTeLab/mbart-summarization-fanpage | 7812dc1714de58152c634f88a19c7eb2a6045e3b | 2022-05-03T06:07:47.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"it",
"dataset:ARTeLab/fanpage",
"transformers",
"summarization",
"model-index",
"autotrain_compatible"
] | summarization | false | ARTeLab | null | ARTeLab/mbart-summarization-fanpage | 70 | null | transformers | 5,370 | ---
tags:
- summarization
language:
- it
metrics:
- rouge
model-index:
- name: summarization_mbart_fanpage4epoch
results: []
datasets:
- ARTeLab/fanpage
---
# mbart-summarization-fanpage
This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on Fanpage da... |
AhmedBou/TuniBert | 615e28c7b0bb3c941092293ccd33ca7cd824b627 | 2021-10-05T01:47:35.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | AhmedBou | null | AhmedBou/TuniBert | 70 | null | transformers | 5,371 | Entry not found |
Helsinki-NLP/opus-mt-cpp-en | 523c5f73e933411d9106072f70a53f4f416685cc | 2021-01-18T07:54:45.000Z | [
"pytorch",
"marian",
"text2text-generation",
"id",
"cpp",
"en",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-cpp-en | 70 | null | transformers | 5,372 | ---
language:
- id
- cpp
- en
tags:
- translation
license: apache-2.0
---
### cpp-eng
* source group: Creoles and pidgins, Portuguese-based
* target group: English
* OPUS readme: [cpp-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cpp-eng/README.md)
* model: transformer
* source lan... |
Helsinki-NLP/opus-mt-fr-ms | 0fd5c97c9aea1f88f99f1636982864a01e57d895 | 2021-01-18T08:45:45.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fr",
"ms",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-fr-ms | 70 | null | transformers | 5,373 | ---
language:
- fr
- ms
tags:
- translation
license: apache-2.0
---
### fra-msa
* source group: French
* target group: Malay (macrolanguage)
* OPUS readme: [fra-msa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-msa/README.md)
* model: transformer-align
* source language(s): fra
* t... |
Helsinki-NLP/opus-mt-vi-it | b505bfc06a5df56401a8206679e920b3898cc004 | 2020-08-21T14:42:51.000Z | [
"pytorch",
"marian",
"text2text-generation",
"vi",
"it",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-vi-it | 70 | null | transformers | 5,374 | ---
language:
- vi
- it
tags:
- translation
license: apache-2.0
---
### vie-ita
* source group: Vietnamese
* target group: Italian
* OPUS readme: [vie-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/vie-ita/README.md)
* model: transformer-align
* source language(s): vie
* target lang... |
OthmaneJ/distil-wav2vec2 | e7d240706c12f07b823716eae6589c79d80ed72f | 2021-08-25T07:59:39.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:librispeech_asr",
"arxiv:2006.11477",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | OthmaneJ | null | OthmaneJ/distil-wav2vec2 | 70 | 7 | transformers | 5,375 | ---
language: en
datasets:
- librispeech_asr
tags:
- speech
- audio
- automatic-speech-recognition
license: apache-2.0
---
# Distil-wav2vec2
This model is a distilled version of the wav2vec2 model (https://arxiv.org/pdf/2006.11477.pdf). This model is 45% times smaller and twice as fast as the original wav2vec2 base m... |
it5/it5-large-news-summarization | 4e7864b2ee439fc04a53d44b93da81a5720094fb | 2022-03-09T07:53:26.000Z | [
"pytorch",
"tf",
"jax",
"tensorboard",
"t5",
"text2text-generation",
"it",
"dataset:ARTeLab/fanpage",
"dataset:ARTeLab/ilpost",
"arxiv:2203.03759",
"transformers",
"italian",
"sequence-to-sequence",
"fanpage",
"ilpost",
"summarization",
"license:apache-2.0",
"model-index",
"co2_e... | summarization | false | it5 | null | it5/it5-large-news-summarization | 70 | null | transformers | 5,376 | ---
language:
- it
license: apache-2.0
datasets:
- ARTeLab/fanpage
- ARTeLab/ilpost
tags:
- italian
- sequence-to-sequence
- fanpage
- ilpost
- summarization
widget:
- text: "Non lo vuole sposare. E’ quanto emerge all’interno dell’ultima intervista di Raffaella Fico che, ringraziando Mancini per i buoni consigli elargi... |
jiangg/chembert_cased | 6764448f64f869e2698ae20f64437feb9cb12f2c | 2021-08-12T18:25:26.000Z | [
"pytorch",
"transformers"
] | null | false | jiangg | null | jiangg/chembert_cased | 70 | 3 | transformers | 5,377 | This is the pre-trained model presented in [Automated Chemical Reaction Extraction from Scientific Literature](https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.1c00284), which is a BERT model trained on chemical literature data.
The training corpus was taken from ~200K ACS publications, more details can be found in the... |
lewtun/oz-fauna | cca6e3688e27fb69df3f4dfc91bc8a46a9ce5017 | 2021-07-01T15:25:24.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | lewtun | null | lewtun/oz-fauna | 70 | null | transformers | 5,378 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: oz-fauna
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8571428656578064
---
# oz-fauna
Autogenerated ... |
megagonlabs/bimeanvae-amzn | a5c0af3fe7f313d1b47d6376c1789aea5696e973 | 2021-09-11T00:10:54.000Z | [
"pytorch",
"en",
"transformers",
"summarization",
"license:bsd-3-clause"
] | summarization | false | megagonlabs | null | megagonlabs/bimeanvae-amzn | 70 | null | transformers | 5,379 | ---
language: en
tags:
- summarization
inference: false
license: bsd-3-clause
---
## BiMeanVAE model
See original GitHub repo for more details [here](https://github.com/megagonlabs/coop)
|
ml6team/gpt2-medium-german-finetune-oscar | 80aa19302f16278286d4917d763413d480d1ed21 | 2021-05-23T09:45:30.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"de",
"transformers",
"adaption",
"recycled",
"gpt2-medium"
] | text-generation | false | ml6team | null | ml6team/gpt2-medium-german-finetune-oscar | 70 | 7 | transformers | 5,380 | ---
language: de
widget:
- text: "es wird entschieden, dass es"
tags:
- adaption
- recycled
- gpt2-medium
- gpt2
pipeline_tag: text-generation
---
# German finetuned GPT2 |
othrif/wav2vec2-large-xlsr-moroccan | 198d2b645573e7b2cef5671c15f7f2175e751a36 | 2021-04-15T03:16:32.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ary",
"dataset:mgb5",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | othrif | null | othrif/wav2vec2-large-xlsr-moroccan | 70 | null | transformers | 5,381 | ---
language: ary
datasets:
- mgb5
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Moroccan Arabic dialect by Othmane Rifki
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
... |
p208p2002/gpt2-squad-qg-hl | 393382bf4dd5c8ffc6b990c3f2acf9b328af079c | 2021-05-23T10:54:57.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"dataset:squad",
"arxiv:1606.05250",
"arxiv:1705.00106",
"transformers",
"question-generation"
] | text-generation | false | p208p2002 | null | p208p2002/gpt2-squad-qg-hl | 70 | null | transformers | 5,382 | ---
datasets:
- squad
tags:
- question-generation
widget:
- text: "Harry Potter is a series of seven fantasy novels written by British author, [HL]J. K. Rowling[HL]."
---
# Transformer QG on SQuAD
HLQG is Proposed by [Ying-Hong Chan & Yao-Chung Fan. (2019). A Re-current BERT-based Model for Question Generation.](https... |
pszemraj/gpt-neo-tiny-JIBA | 1671445eaa67954f7b22abfdf21c32293aef7a6c | 2022-02-01T23:33:04.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"generated_from_trainer",
"gpt-neo",
"license:apache-2.0"
] | text-generation | false | pszemraj | null | pszemraj/gpt-neo-tiny-JIBA | 70 | null | transformers | 5,383 | ---
license: apache-2.0
tags:
- generated_from_trainer
- gpt-neo
widget:
- text: "waddup bro?\n"
example_title: "waddup"
- text: "Are you going to be on League tonight?\n"
example_title: "League"
- text: "One of my hot takes is that dogs are cute. What do you think?\n"
example_title: "hot take"
- text: "what... |
skimai/spanberta-base-cased-ner-conll02 | dbaa1f489188897b4232c70825cbfa12bba275bb | 2021-05-20T21:50:52.000Z | [
"pytorch",
"jax",
"roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | skimai | null | skimai/spanberta-base-cased-ner-conll02 | 70 | null | transformers | 5,384 | Entry not found |
uclanlp/plbart-c-cpp-defect-detection | 51fe64169b0e3da9086766747b6be33f523636b9 | 2021-11-09T17:18:32.000Z | [
"pytorch",
"plbart",
"text-classification",
"transformers"
] | text-classification | false | uclanlp | null | uclanlp/plbart-c-cpp-defect-detection | 70 | null | transformers | 5,385 | Entry not found |
youzanai/clip-product-title-chinese | 4bbf81603024c2c2b4f19c4fc2babdf2e1d32679 | 2022-02-09T08:59:51.000Z | [
"pytorch",
"clip_chinese_model",
"transformers"
] | null | false | youzanai | null | youzanai/clip-product-title-chinese | 70 | 5 | transformers | 5,386 | <!--
* @Description:
* @Version:
* @Author: Hardy
* @Date: 2022-02-09 15:13:53
* @LastEditors: Hardy
* @LastEditTime: 2022-02-09 16:59:01
-->
<br />
<p align="center">
<h1 align="center">clip-product-title-chinese</h1>
</p>
## 基于有赞商品图片和标题语料训练的clip模型。
## Usage
使用模型前，请 git clone https://github.com/youzanai/... |
nntadotzips/bert-base-cased-SynonymReplacementMethod_5703sem0of1to1999and5000to7162__8627sem1 | 2631131d1f6e1d982bcbf079d93a91af235b478c | 2022-03-17T10:51:04.000Z | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | false | nntadotzips | null | nntadotzips/bert-base-cased-SynonymReplacementMethod_5703sem0of1to1999and5000to7162__8627sem1 | 70 | null | transformers | 5,387 | Entry not found |
mcsabai/huBert-fine-tuned-hungarian-squadv1 | 4d72ef9cbd028f38d67dc46f70215387e97c3fda | 2022-05-10T10:59:53.000Z | [
"pytorch",
"tf",
"bert",
"question-answering",
"hu",
"transformers",
"autotrain_compatible"
] | question-answering | false | mcsabai | null | mcsabai/huBert-fine-tuned-hungarian-squadv1 | 70 | 1 | transformers | 5,388 | ---
language: hu
thumbnail:
tags:
- question-answering
- bert
widget:
- text: "Melyik folyó szeli ketté Budapestet?"
context: "Magyarország fővárosát, Budapestet a Duna folyó szeli ketté. A XIX. században épült Lánchíd a dimbes-dombos budai oldalt köti össze a sík Pesttel. A Várdomb oldalában futó siklóval juthatunk... |
johnnydevriese/vit_beans | 3121791c03bfb93ee61a48d5b995b485e400cb89 | 2022-04-01T02:24:41.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:beans",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | johnnydevriese | null | johnnydevriese/vit_beans | 70 | null | transformers | 5,389 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: vit_beans
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
metrics:
- name: Accuracy
... |
dimbyTa/rock-challenge-DeiT-solo-2 | ae8f0b5b82a70cdc53b49a71f46097ad3354a53e | 2022-04-23T15:54:30.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | dimbyTa | null | dimbyTa/rock-challenge-DeiT-solo-2 | 70 | null | transformers | 5,390 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rock-challenge-DeiT-solo-2
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8100078105926514
---
# rock-ch... |
csebuetnlp/banglishbert | 88f2777acd65160b2a6c07e5ffef2d232daadf87 | 2022-05-10T05:13:47.000Z | [
"pytorch",
"electra",
"pretraining",
"bn",
"en",
"arxiv:2101.00204",
"transformers"
] | null | false | csebuetnlp | null | csebuetnlp/banglishbert | 70 | null | transformers | 5,391 | ---
language:
- bn
- en
licenses:
- cc-by-nc-sa-4.0
---
# BanglishBERT
This repository contains the pretrained discriminator checkpoint of the model **BanglishBERT**. This is an [ELECTRA](https://openreview.net/pdf?id=r1xMH1BtvB) discriminator model pretrained with the Replaced Token Detection (RTD) objective on lar... |
aricibo/swin-tiny-patch4-window7-224-finetuned-eurosat | 611dcdf9bd96368abcf00d9f1a058aa73c861344 | 2022-05-20T07:48:24.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | aricibo | null | aricibo/swin-tiny-patch4-window7-224-finetuned-eurosat | 70 | null | transformers | 5,392 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
... |
schoenml/swin-tiny-patch4-window7-224-finetuned-eurosat | 100220f08c12c20b02f40ec9de2ca6486756b222 | 2022-05-25T15:56:50.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | schoenml | null | schoenml/swin-tiny-patch4-window7-224-finetuned-eurosat | 70 | null | transformers | 5,393 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete ... |
DaBaap/Chat-Bot-Batman | 5dcf5b5c1043435e7fe25fe75c0bddafb92c96ce | 2022-05-27T23:13:47.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | DaBaap | null | DaBaap/Chat-Bot-Batman | 70 | null | transformers | 5,394 | ---
tags:
- conversational
--- |
mrm8488/bertin-gpt-j-6B-ES-8bit | d87f4e9ad6d12594788bda91ddeac3c6f8efce21 | 2022-06-03T11:35:42.000Z | [
"pytorch",
"gptj",
"text-generation",
"es",
"arxiv:2106.09685",
"arxiv:2110.02861",
"transformers",
"gpt-j",
"spanish",
"gpt-j-6b",
"license:wtfpl"
] | text-generation | false | mrm8488 | null | mrm8488/bertin-gpt-j-6B-ES-8bit | 70 | 2 | transformers | 5,395 | ---
license: wtfpl
language: es
tags:
- gpt-j
- spanish
- gpt-j-6b
---
# BERTIN-GPT-J-6B with 8-bit weights (Quantized)
This model (and model card) is an adaptation of [hivemind/gpt-j-6B-8bit](https://huggingface.co/hivemind/gpt-j-6B-8bit), so all credits to him/her.
This is a version of **bertin-project/bertin-gpt-... |
facebook/genre-kilt | d5c718b8bb571121a0d74d5bbc9a1d69a9a9c312 | 2022-06-14T14:05:20.000Z | [
"pytorch",
"tf",
"jax",
"bart",
"text2text-generation",
"en",
"arxiv:2010.00904",
"arxiv:1910.13461",
"arxiv:2009.02252",
"transformers",
"retrieval",
"entity-retrieval",
"named-entity-disambiguation",
"entity-disambiguation",
"named-entity-linking",
"entity-linking",
"autotrain_comp... | text2text-generation | false | facebook | null | facebook/genre-kilt | 70 | null | transformers | 5,396 | ---
language:
- en
tags:
- retrieval
- entity-retrieval
- named-entity-disambiguation
- entity-disambiguation
- named-entity-linking
- entity-linking
- text2text-generation
---
# GENRE
The GENRE (Generative ENtity REtrieval) system as presented in [Autoregressive Entity Retrieval](https://arxiv.org/abs/2010.00904... |
microsoft/markuplm-large-finetuned-websrc | a9fe69d1cb7a60734e3bc18060edcf0b4b9310ee | 2022-06-14T13:57:35.000Z | [
"pytorch",
"markuplm",
"question-answering",
"arxiv:2110.08518",
"transformers",
"autotrain_compatible"
] | question-answering | false | microsoft | null | microsoft/markuplm-large-finetuned-websrc | 70 | null | transformers | 5,397 | # 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... |
prodm93/bert-rp-1-sentchunks | 91e55fc4c609a6bc40ba7533e35128683d375131 | 2022-07-04T19:21:23.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | prodm93 | null | prodm93/bert-rp-1-sentchunks | 70 | null | transformers | 5,398 | Entry not found |
cybertelx/DialoGPT-small-drunkic0n | b31eccbc3cec34289e091cc506e53c23bf47fc71 | 2022-07-14T14:45:10.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | cybertelx | null | cybertelx/DialoGPT-small-drunkic0n | 70 | null | transformers | 5,399 | ---
tags:
- conversational
---
# Drunk IC-0n
IC-0n (or Icon) is a murderous AI protagonist of the Internecion Cube series. This is an attempt to build her in real life (haha it failed, and actually gladly)
This uses Microsoft's DialoGPT-small and it is trained on all of Icon's lines throughout the series from episod... |
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