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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
mrm8488/t5-base-finetuned-break_data-question-retrieval | b4df506ab5b6e6ad17fc80e82e40f469234a1467 | 2021-08-20T10:57:21.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:break_data",
"arxiv:1910.10683",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | mrm8488 | null | mrm8488/t5-base-finetuned-break_data-question-retrieval | 82 | 1 | transformers | 5,000 | ---
language: en
datasets:
- break_data
widget:
- text: "translate QDMRs to Natural Language return the city that was the birthplace of Bernard Berrian ;return the city that was the home of Pablo Picasso ;return the city of both #1 and #2"
---
# T5-base fine-tuned on break_data / QDMR-high-level 📋➡️❓
[Google's ... |
philippelaban/summary_loop46 | 7216900e899706902b91c352c74fd2a06540f1d1 | 2022-02-09T21:59:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"dataset:cnn_dailymail",
"transformers",
"summarization",
"license:apache-2.0"
] | summarization | false | philippelaban | null | philippelaban/summary_loop46 | 82 | 3 | transformers | 5,001 | ---
language:
- en
tags:
- summarization
license: apache-2.0
datasets:
- cnn_dailymail
metrics:
- rouge
---
# Try out in the Hosted inference API
In the right panel, you can try to the model (although it only handles a short sequence length).
Enter the document you want to summarize in the panel on the right.
# Mode... |
roschmid/dog-races | b859d5551bb15c5341e6fd8e136cc7e36410503c | 2021-07-27T17:32:40.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | roschmid | null | roschmid/dog-races | 82 | 1 | transformers | 5,002 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: dog-races-v2
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8299999833106995
---
# dog-races-v2
Autoge... |
textattack/distilbert-base-uncased-ag-news | 52ee64de95f38323f136c6f6b05e1af7c433417e | 2020-07-07T22:01:14.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/distilbert-base-uncased-ag-news | 82 | 1 | transformers | 5,003 | ## TextAttack Model CardThis `distilbert-base-uncased` model was fine-tuned for sequence classification using TextAttack
and the ag_news dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 32, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this w... |
stanleychu2/t5-transition | 3188c7352c52d6ee172c050a3346f6a10bfd6635 | 2022-03-07T09:06:03.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | stanleychu2 | null | stanleychu2/t5-transition | 82 | null | transformers | 5,004 | Entry not found |
speeqo/bert-restore-punctuation | f8183291f7a20e1a45aee41e13f7c6e4ec31434e | 2022-03-22T15:01:06.000Z | [
"pytorch",
"bert",
"token-classification",
"en",
"dataset:yelp_polarity",
"transformers",
"punctuation",
"license:mit",
"autotrain_compatible"
] | token-classification | false | speeqo | null | speeqo/bert-restore-punctuation | 82 | null | transformers | 5,005 | ---
language:
- en
tags:
- punctuation
license: mit
datasets:
- yelp_polarity
metrics:
- f1
---
# ✨ bert-restore-punctuation
[]()
This a bert-base-uncased model finetuned for punctuation restoration on [Yelp Reviews](https://www.tensorflow.org/datase... |
abdusahmbzuai/CarViT | f5d9c1fcd97e816238ca2ecd1358f88b446c3354 | 2022-03-26T16:04:39.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | abdusahmbzuai | null | abdusahmbzuai/CarViT | 82 | 1 | transformers | 5,006 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: CarViT
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8122026920318604
---
# CarViT
CarViT - Car make... |
nielsr/vit-finetuned-eurosat-kornia | ee2a32698018189c82f1e539aab24db0c7746287 | 2022-04-20T13:39:39.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers"
] | image-classification | false | nielsr | null | nielsr/vit-finetuned-eurosat-kornia | 82 | null | transformers | 5,007 | Entry not found |
V0ltron/vit-base-patch16-224-finetuned-largerDataSet-docSeperator-more-labels-all-apache2 | 41f483fc2533befd1fc46f6cba3b17c79d1b69e8 | 2022-04-21T22:58:02.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers"
] | image-classification | false | V0ltron | null | V0ltron/vit-base-patch16-224-finetuned-largerDataSet-docSeperator-more-labels-all-apache2 | 82 | null | transformers | 5,008 | Entry not found |
smc/electric_poles | ad1c09f5e921cf6eecc86a2bb0c46b17f1ef72e9 | 2022-05-14T23:57:32.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers"
] | image-classification | false | smc | null | smc/electric_poles | 82 | null | transformers | 5,009 | |
lucataco/DialoGPT-medium-rafa | 4356fdc9908a0ebf4baf0d0f797934e30a909dad | 2022-07-03T23:35:53.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | lucataco | null | lucataco/DialoGPT-medium-rafa | 82 | null | transformers | 5,010 | ---
tags:
- conversational
---
# Rafa Dialog GPT Model Medium 10
# Trained on discord channels:
# half of Dragalia chat |
ysnow9876/alephbert-base-finetuned-for-shut | be31ccba32f71b80bbeb4e3d2af181550268a4fa | 2022-07-07T10:24:25.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | ysnow9876 | null | ysnow9876/alephbert-base-finetuned-for-shut | 82 | null | transformers | 5,011 | **AlephBERT-base-finetuned-for-shut**
**Hebrew Language Model**
Based on alephbert-base: https://huggingface.co/onlplab/alephbert-base#alephbert
**How to use:**
from transformers import AutoModelForMaskedLM, AutoTokenizer
checkpoint = 'ysnow9876/alephbert-base-finetuned-for-shut'
tokenizer = AutoTokenizer.from_p... |
cointegrated/rut5-base-labse-decoder | b618b3be48c6e3a181be9820773f645df7572346 | 2022-07-18T21:45:00.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ru",
"transformers",
"russian",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | cointegrated | null | cointegrated/rut5-base-labse-decoder | 82 | 2 | transformers | 5,012 | ---
language: ["ru"]
tags:
- russian
license: mit
---
This is the [rut5-base](https://huggingface.co/cointegrated/rut5-base) model, with the decoder fine-tuned to recover (approximately) Russian sentences from their [LaBSE](https://huggingface.co/sentence-transformers/LaBSE) embeddings. Details are [here](https://habr... |
thefrigidliquidation/nllb-200-distilled-1.3B-bookworm | 9ab5bc19236a26b1bcf5d71d2af6e27a52e9f671 | 2022-07-27T22:44:57.000Z | [
"pytorch",
"m2m_100",
"text2text-generation",
"en",
"ja",
"transformers",
"nllb",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | text2text-generation | false | thefrigidliquidation | null | thefrigidliquidation/nllb-200-distilled-1.3B-bookworm | 82 | null | transformers | 5,013 | ---
language:
- en
- ja
tags:
- nllb
license: cc-by-nc-4.0
---
# NLLB-200 1.3B fine-tuned on Ascendance of a Bookworm
This model was fine-tuned on Ascendance of a Bookworm to translate the web novel in Japanese to English. |
Finnish-NLP/roberta-large-finnish-v2 | 968ba8c12c1513ca4d57ddf40f24c6c40817280f | 2022-06-13T16:11:54.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"fi",
"dataset:Finnish-NLP/mc4_fi_cleaned",
"dataset:wikipedia",
"arxiv:1907.11692",
"transformers",
"finnish",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Finnish-NLP | null | Finnish-NLP/roberta-large-finnish-v2 | 81 | null | transformers | 5,014 | ---
language:
- fi
license: apache-2.0
tags:
- finnish
- roberta
datasets:
- Finnish-NLP/mc4_fi_cleaned
- wikipedia
widget:
- text: "Moikka olen <mask> kielimalli."
---
# RoBERTa large model for Finnish
This **Finnish-NLP/roberta-large-finnish-v2** model is a new version of the previously trained [Finnish-NLP/robert... |
Helsinki-NLP/opus-mt-he-es | 7f5a141ef9fbceef7c5f5f175e7faee77ac548ac | 2021-01-18T08:54:30.000Z | [
"pytorch",
"marian",
"text2text-generation",
"he",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-he-es | 81 | null | transformers | 5,015 | ---
language:
- he
- es
tags:
- translation
license: apache-2.0
---
### he-es
* source group: Hebrew
* target group: Spanish
* OPUS readme: [heb-spa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/heb-spa/README.md)
* model: transformer
* source language(s): heb
* target language(s): spa
*... |
Helsinki-NLP/opus-mt-ja-fr | 2d413788b9ad1f7bd29dba9c38871bab9c29cf2d | 2021-09-10T13:53:24.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-fr | 81 | null | transformers | 5,016 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-ja-fr
* source languages: ja
* target languages: fr
* OPUS readme: [ja-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ja-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
IlyaGusev/rugpt3medium_sum_gazeta | 2de06384e4ce5e24d78fce769e94cc524eaf09e8 | 2022-07-13T15:36:49.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"dataset:IlyaGusev/gazeta",
"transformers",
"causal-lm",
"summarization",
"license:apache-2.0"
] | summarization | false | IlyaGusev | null | IlyaGusev/rugpt3medium_sum_gazeta | 81 | null | transformers | 5,017 | ---
language:
- ru
tags:
- causal-lm
- summarization
datasets:
- IlyaGusev/gazeta
license:
- apache-2.0
inference: false
widget:
- text: "Высота башни составляет 324 метра (1063 фута), примерно такая же высота, как у 81-этажного здания, и самое высокое сооружение в Париже. Его основание квадратно, размером 125 метров (... |
Kayvane/distilbert-complaints-product | 1e6557e5f43f098977dd4a9232ca3c77883488f0 | 2022-01-30T19:15:13.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:consumer_complaints",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | Kayvane | null | Kayvane/distilbert-complaints-product | 81 | null | transformers | 5,018 | ---
tags:
- generated_from_trainer
datasets:
- consumer_complaints
model-index:
- name: distilbert-complaints-product
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. ... |
akahana/asl-vit | 0eb0268bab48b7e79853ccf3efb538c77318143c | 2021-12-23T01:39:37.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers"
] | image-classification | false | akahana | null | akahana/asl-vit | 81 | null | transformers | 5,019 | Entry not found |
cardiffnlp/twitter-roberta-base-dec2021 | 3a48992ecb684089d7462039f7bd1e1b57c6912f | 2022-02-09T11:16:45.000Z | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.03829",
"transformers",
"autotrain_compatible"
] | fill-mask | false | cardiffnlp | null | cardiffnlp/twitter-roberta-base-dec2021 | 81 | null | transformers | 5,020 | # Twitter December 2021 (RoBERTa-base, 124M)
This is a RoBERTa-base model trained on 123.86M tweets until the end of December 2021.
More details and performance scores are available in the [TimeLMs paper](https://arxiv.org/abs/2202.03829).
Below, we provide some usage examples using the standard Transformers interfac... |
facebook/convnext-base-224-22k-1k | 10155e7aac169400ee90dc25762ebc353efa855d | 2022-03-02T19:04:07.000Z | [
"pytorch",
"tf",
"convnext",
"image-classification",
"dataset:imagenet-21k",
"dataset:imagenet-1k",
"arxiv:2201.03545",
"transformers",
"vision",
"license:apache-2.0"
] | image-classification | false | facebook | null | facebook/convnext-base-224-22k-1k | 81 | null | transformers | 5,021 | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- imagenet-21k
- imagenet-1k
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teap... |
huggingtweets/pokimanelol | e7409dc6f755e18bf678d35483890f1f2ba68671 | 2021-05-22T18:58:06.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/pokimanelol | 81 | null | transformers | 5,022 | ---
language: en
thumbnail: https://www.huggingtweets.com/pokimanelol/1618687549011/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/1375208359792... |
racai/distilbert-base-romanian-cased | b6eedd204dfac801abf100f33b458b0c2f62e3e3 | 2021-12-24T17:22:46.000Z | [
"pytorch",
"tf",
"jax",
"distilbert",
"ro",
"dataset:oscar",
"dataset:wikipedia",
"arxiv:2112.12650",
"transformers",
"license:mit"
] | null | false | racai | null | racai/distilbert-base-romanian-cased | 81 | null | transformers | 5,023 | ---
language: ro
license: mit
datasets:
- oscar
- wikipedia
---
# Romanian DistilBERT
This repository contains the uncased Romanian DistilBERT (named Distil-BERT-base-ro in the paper). The teacher model used for distillation is: [dumitrescustefan/bert-base-romanian-cased-v1](https://huggingface.co/dumitrescustefan/be... |
sentence-transformers/nli-bert-large-cls-pooling | c43e5c61903eeffe993e572eaa70b9918c310dee | 2022-06-16T01:01:45.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/nli-bert-large-cls-pooling | 81 | null | sentence-transformers | 5,024 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
**⚠️ This model is deprecated. Please don't use it as it produces sentence embeddings of low quality. You can find recommended sentence embedding models here: [SBERT.net... |
smaranjitghose/cricket-baseball-smrn | 21dc18049cea299be596c4f155bf5f77bd723731 | 2021-07-02T05:54:21.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | smaranjitghose | null | smaranjitghose/cricket-baseball-smrn | 81 | null | transformers | 5,025 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: cricket-baseball-smrn
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9791666865348816
---
# cricket-base... |
uer/chinese_roberta_L-6_H-256 | 49ad049362c35d8dea318c05213217b97d1644bc | 2022-07-15T08:13:06.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"zh",
"dataset:CLUECorpusSmall",
"arxiv:1909.05658",
"arxiv:1908.08962",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uer | null | uer/chinese_roberta_L-6_H-256 | 81 | 1 | transformers | 5,026 | ---
language: zh
datasets: CLUECorpusSmall
widget:
- text: "北京是[MASK]国的首都。"
---
# Chinese RoBERTa Miniatures
## Model description
This is the set of 24 Chinese RoBERTa models pre-trained by [UER-py](https://github.com/dbiir/UER-py/), which is introduced in [this paper](https://arxiv.org/abs/1909.05658).
[Turc e... |
uer/roberta-base-finetuned-ifeng-chinese | f72929ec3b231a1888859ae53c5b2710a5ce1cfa | 2022-02-20T07:57:39.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"zh",
"arxiv:1909.05658",
"arxiv:1708.02657",
"transformers"
] | text-classification | false | uer | null | uer/roberta-base-finetuned-ifeng-chinese | 81 | null | transformers | 5,027 | ---
language: zh
widget:
- text: "这本书真的很不错"
---
# Chinese RoBERTa-Base Models for Text Classification
## Model description
This is the set of 5 Chinese RoBERTa-Base classification models fine-tuned by [UER-py](https://arxiv.org/abs/1909.05658). You can download the 5 Chinese RoBERTa-Base classification models eith... |
lewiswatson/distilbert-base-uncased-finetuned-emotion | ae30dc7fb3468a92450e6f354bfbcf03158e26a1 | 2022-07-13T22:43:00.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | lewiswatson | null | lewiswatson/distilbert-base-uncased-finetuned-emotion | 81 | 1 | transformers | 5,028 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
johnnydevriese/vliegmachine | 405745790a3b160e8d88581a5f7637acdc6d088d | 2022-04-02T02:54:43.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | johnnydevriese | null | johnnydevriese/vliegmachine | 81 | null | transformers | 5,029 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: vliegmachine
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.5970149040222168
---
# vliegmachine
Autoge... |
AykeeSalazar/violation-classification-bantai-vit-v80ep | 1a2c9af687c9b4ec0cd1d365484da8b799f9cec6 | 2022-04-03T23:45:50.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | AykeeSalazar | null | AykeeSalazar/violation-classification-bantai-vit-v80ep | 81 | null | transformers | 5,030 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: violation-classification-bantai-vit-v80ep
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
a... |
QCRI/bert-base-multilingual-cased-chunking-english | 2239da76edb70fe23d753de156ea90069c56f089 | 2022-04-27T08:42:55.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"license:cc-by-nc-4.0",
"autotrain_compatible"
] | token-classification | false | QCRI | null | QCRI/bert-base-multilingual-cased-chunking-english | 81 | null | transformers | 5,031 | ---
license: cc-by-nc-4.0
---
|
qanastek/XLMRoberta-Alexa-Intents-NER-NLU | f45f70779485ea8efa5df00811f4bae2a30a2499 | 2022-05-09T07:02:36.000Z | [
"pytorch",
"dataset:qanastek/MASSIVE",
"Transformers",
"Token Classification",
"Slot Annotation",
"token-classification",
"sequence-tagger-model",
"license:cc-by-4.0"
] | token-classification | false | qanastek | null | qanastek/XLMRoberta-Alexa-Intents-NER-NLU | 81 | 1 | null | 5,032 | ---
tags:
- Transformers
- Token Classification
- Slot Annotation
- token-classification
- sequence-tagger-model
languages:
- af-ZA
- am-ET
- ar-SA
- az-AZ
- bn-BD
- cy-GB
- da-DK
- de-DE
- el-GR
- en-US
- es-ES
- fa-IR
- fi-FI
- fr-FR
- he-IL
- hi-IN
- hu-HU
- hy-AM
- id-ID
- is-IS
- it-IT
- ja-JP
- jv-ID
- ka-GE
- km... |
smc/electric | 571c81e106b58a0995485cfab9271ba4a6c0d4b4 | 2022-05-15T00:19:16.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | smc | null | smc/electric | 81 | null | transformers | 5,033 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: electric
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9166666865348816
---
# electric
Autogenerated ... |
dipstheman/DialoGPT-small-humanconversationpart | 23cf20a46b2603902e30c6d937360e301b62205f | 2022-05-16T22:26:11.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | dipstheman | null | dipstheman/DialoGPT-small-humanconversationpart | 81 | null | transformers | 5,034 | ---
tags:
- conversational
---
# human conversation part DialoGPT Model |
sumedh/t5-base-amazonreviews | b7f796ab80907ee936d841889feee697a7f33d99 | 2022-05-22T23:19:09.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:amazon_reviews_multi",
"transformers",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | sumedh | null | sumedh/t5-base-amazonreviews | 81 | null | transformers | 5,035 | ---
language:
- en
datasets:
- amazon_reviews_multi
tags:
- summarization
license: apache-2.0
---
T5-base model for text summarization finetuned on subset of amazon reviews for english language.
## Rouge scores
- Rouge 1 : 0.5019
- Rouge 2 : 0.4226
- Rouge L : 0.4877
- Rouge Lsum : 0.4877 |
pszemraj/opt-peter-2.7B | ea9a4f7c226b798e61c0d07004599c281564d277 | 2022-07-15T00:32:37.000Z | [
"pytorch",
"opt",
"text-generation",
"transformers",
"generated_from_trainer",
"non-commercial",
"dialogue",
"chatbot",
"license:apache-2.0"
] | text-generation | false | pszemraj | null | pszemraj/opt-peter-2.7B | 81 | null | transformers | 5,036 | ---
license: apache-2.0
tags:
- generated_from_trainer
- text-generation
- opt
- non-commercial
- dialogue
- chatbot
inference: false
---
# pszemraj/opt-peter-2.7B
This model is a fine-tuned version of [facebook/opt-2.7b](https://huggingface.co/facebook/opt-2.7b) on about 80k whatsapp/text messages (mine). Please us... |
casperthegazer/DialoGT-gandalf-urdot | 55658dd3f3e98dc57f7653b1f7fb734b6770578c | 2022-07-16T22:12:00.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | casperthegazer | null | casperthegazer/DialoGT-gandalf-urdot | 81 | null | transformers | 5,037 | ---
tags:
- conversational
---
# Uriel Dot DialoGT Model |
TeaTM/DialoGPT-small-bushcat | ab3445999813d8e1ae8998b3b4e31d1d0587ff19 | 2022-07-19T23:36:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | TeaTM | null | TeaTM/DialoGPT-small-bushcat | 81 | null | transformers | 5,038 | ---
tags:
- conversational
---
# Bushcat DialoGPT Model |
AkshatSurolia/BEiT-FaceMask-Finetuned | f519ddc8760cde578c4c4e77fc01ed3cfe25b010 | 2022-02-18T13:40:53.000Z | [
"pytorch",
"beit",
"image-classification",
"dataset:Face-Mask18K",
"transformers",
"license:apache-2.0"
] | image-classification | false | AkshatSurolia | null | AkshatSurolia/BEiT-FaceMask-Finetuned | 80 | null | transformers | 5,039 | ---
license: apache-2.0
tags:
- image-classification
datasets:
- Face-Mask18K
---
# BEiT for Face Mask Detection
BEiT model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was introduced in the paper BEIT: BERT Pre-Training of Image ... |
Helsinki-NLP/opus-mt-ko-fr | 434c8db99c855e569705f74437c99a42a5dba649 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ko",
"fr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ko-fr | 80 | null | transformers | 5,040 | ---
language:
- ko
- fr
tags:
- translation
license: apache-2.0
---
### kor-fra
* source group: Korean
* target group: French
* OPUS readme: [kor-fra](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/kor-fra/README.md)
* model: transformer-align
* source language(s): kor kor_Hang kor_Hani ... |
IlyaGusev/rubertconv_toxic_editor | 639cbff7dfed795af239941b960511fa9292ae2e | 2022-07-13T15:33:55.000Z | [
"pytorch",
"bert",
"token-classification",
"ru",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | IlyaGusev | null | IlyaGusev/rubertconv_toxic_editor | 80 | 3 | transformers | 5,041 | ---
language:
- ru
tags:
- token-classification
license: apache-2.0
widget:
- text: Ёпта, меня зовут придурок и я живу в жопе
---
# RuBERTConv Toxic Editor
## Model description
Tagging model for detoxification based on [rubert-base-cased-conversational](https://huggingface.co/DeepPavlov/rubert-base-cased-conversa... |
Intel/distilbert-base-uncased-sparse-90-unstructured-pruneofa | 98edb13b564abca84d51e5c2c908db0904a29ac8 | 2021-12-05T13:39:57.000Z | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"en",
"arxiv:2111.05754",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Intel | null | Intel/distilbert-base-uncased-sparse-90-unstructured-pruneofa | 80 | 1 | transformers | 5,042 | ---
language: en
---
# 90% Sparse DistilBERT-Base (uncased) Prune OFA
This model is a result from our paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754) presented in ENLSP NeurIPS Workshop 2021.
For further details on the model and its result, see our paper and our impleme... |
LorenzoDeMattei/lawn-weeds | 6fcb4df8e534e57d9d15c816e5f03ab394994a8c | 2021-07-02T10:07:36.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | LorenzoDeMattei | null | LorenzoDeMattei/lawn-weeds | 80 | null | transformers | 5,043 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: lawn-weeds
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9166666865348816
---
# lawn-weeds
Autogenera... |
Suzana/new-york-tokyo-london | 94f338dd2a9912338fb64f316c4bbd91ab80c7af | 2022-01-13T17:53:58.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Suzana | null | Suzana/new-york-tokyo-london | 80 | 1 | transformers | 5,044 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: new-york-tokyo-london
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9104477763175964
---
# new-york-tok... |
accelotron/rugpt3-ficbook-bts | bc698b9a6170e7fac5c851a4a7e94aaea75f04ab | 2021-07-06T18:08:59.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | accelotron | null | accelotron/rugpt3-ficbook-bts | 80 | 1 | transformers | 5,045 | ruGPT-3 fine-tuned on russian fanfiction about Bangatan Boys (BTS). |
adilism/wav2vec2-large-xlsr-kazakh | 526fb635fb982632eef3ba76c63db495fc79b6c9 | 2021-07-05T18:45:44.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"kk",
"dataset:kazakh_speech_corpus",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | adilism | null | adilism/wav2vec2-large-xlsr-kazakh | 80 | null | transformers | 5,046 | ---
language: kk
datasets:
- kazakh_speech_corpus
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: Wav2Vec2-XLSR-53 Kazakh by adilism
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dat... |
amirhossein1376/pft-clf-finetuned | 443147107a873f99452a7dd79c5ac3ef976b0e47 | 2021-11-13T09:50:27.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"fa",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | amirhossein1376 | null | amirhossein1376/pft-clf-finetuned | 80 | 1 | transformers | 5,047 | ---
license: apache-2.0
language: fa
widget:
- text: "امروز دربی دو تیم پرسپولیس و استقلال در ورزشگاه آزادی تهران برگزار میشود."
- text: "وزیر امور خارجه اردن تاکید کرد که همه کشورهای عربی خواهان روابط خوب با ایران هستند.
به گزارش ایسنا به نقل از شبکه فرانس ۲۴، ایمن الصفدی معاون نخستوزیر و وزیر امور خارجه اردن پس ... |
dbmdz/electra-small-turkish-cased-generator | f40bcdce25cd4c2b66bab32f4d361fa9db85f53e | 2020-05-12T21:54:17.000Z | [
"pytorch",
"tf",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/electra-small-turkish-cased-generator | 80 | null | transformers | 5,048 | Entry not found |
huggingtweets/fartydoodooman | db2539a031b8197f04edd4ef9fb1d6f2c56f0ad0 | 2021-05-22T03:54:38.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/fartydoodooman | 80 | null | transformers | 5,049 | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
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/1330826... |
jpcorb20/pegasus-large-reddit_tifu-samsum-512 | 37ac972a0cc599ca653dc39d38995f8810dea43e | 2021-03-26T12:59:56.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"en",
"dataset:samsum",
"transformers",
"google/pegasus-reddit_tifu",
"summarization",
"samsum",
"autotrain_compatible"
] | summarization | false | jpcorb20 | null | jpcorb20/pegasus-large-reddit_tifu-samsum-512 | 80 | null | transformers | 5,050 | ---
language:
- en
thumbnail:
tags:
- pytorch
- google/pegasus-reddit_tifu
- summarization
- samsum
license:
datasets:
- samsum
metrics:
- rouge
---
# Samsum Pegasus (Reddit/TIFU) for conversational summaries
## Model description
Pegasus (Reddit/TIFU) for conversational summaries trained on the samsum dataset!
#... |
lincoln/flaubert-mlsum-topic-classification | 8fb7d948ea8500507d68f5681fd290b138e44757 | 2021-10-14T13:26:57.000Z | [
"pytorch",
"tf",
"flaubert",
"text-classification",
"fr",
"dataset:MLSUM",
"arxiv:2004.14900",
"transformers",
"license:mit"
] | text-classification | false | lincoln | null | lincoln/flaubert-mlsum-topic-classification | 80 | 6 | transformers | 5,051 | ---
language:
- fr
license: mit
datasets:
- MLSUM
pipeline_tag: "text-classification"
widget:
- text: La bourse de paris en forte baisse après que des canards ont envahit le parlement.
tags:
- text-classification
- flaubert
---
# Classification d'articles de presses avec Flaubert
Ce modèle se base sur le modèl... |
macedonizer/mk-roberta-base | eda071f5e775acaaf668d5b30d9f7db3bccb4d06 | 2021-09-22T08:58:49.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"mk",
"dataset:wiki-mk",
"dataset:time-mk-news-2010-2015",
"transformers",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | macedonizer | null | macedonizer/mk-roberta-base | 80 | null | transformers | 5,052 | ---
language:
- mk
thumbnail: https://huggingface.co/macedonizer/mk-roberta-base/blaze-koneski.jpg
tags:
- masked-lm
license: apache-2.0
datasets:
- wiki-mk
- time-mk-news-2010-2015
---
# MK-RoBERTa base model
Pretrained model on Macedonian language using a masked language modeling (MLM) objective. It was introduced i... |
mmekias/vit-base-beans | 4fb1a158ff71dcbdabb2cc56ca60c0c52f4b4feb | 2021-11-26T11:44:38.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers"
] | image-classification | false | mmekias | null | mmekias/vit-base-beans | 80 | null | transformers | 5,053 | Entry not found |
mrm8488/vit-base-patch16-224_finetuned-kvasirv2-colonoscopy | 61fe5d4ca49ace44e55cd69fd708102fc283d796 | 2021-09-07T14:32:12.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"medical",
"colon"
] | image-classification | false | mrm8488 | null | mrm8488/vit-base-patch16-224_finetuned-kvasirv2-colonoscopy | 80 | 3 | transformers | 5,054 | ---
tags:
- image-classification
- pytorch
- medical
- colon
metrics:
- accuracy: 0.93
---
# Vision Transformer fine-tuned on kvasir_v2 for colonoscopy classification
## Demo
### Drag the following images to the widget to test the model
- 
- ![](ht... |
nateraw/denver-nyc-paris | 31fd21c9b0dd81d4b141d09552d1d8691fa18dd1 | 2021-06-30T07:11:34.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nateraw | null | nateraw/denver-nyc-paris | 80 | null | transformers | 5,055 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: denver-nyc-paris
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8657407164573669
---
# denver-nyc-paris
... |
osanseviero/llama-alpaca-guanaco-vicuna | f1f81ffbcb49d1d2fc5919ed32ed8e813e1567a1 | 2022-04-01T09:46:02.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"llama-leaderboard",
"model-index"
] | image-classification | false | osanseviero | null | osanseviero/llama-alpaca-guanaco-vicuna | 80 | 0 | transformers | 5,056 | ---
tags:
- image-classification
- pytorch
- huggingpics
- llama-leaderboard
metrics:
- accuracy
model-index:
- name: llamastic
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.39772728085517883
---
# lla... |
shivkumarganesh/vision-transformer-fmri-classification-ft | 8985b504c7a41f30e9969aa124e6e657f3de83c1 | 2021-11-19T13:21:37.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | shivkumarganesh | null | shivkumarganesh/vision-transformer-fmri-classification-ft | 80 | 1 | transformers | 5,057 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: vision-transformer-fmri-classification-ft
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7955589294433594... |
velociraptor/hugging-doge | 27ff4f203ea09fec44c2168511f10065970ba24e | 2021-08-28T06:01:46.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | velociraptor | null | velociraptor/hugging-doge | 80 | null | transformers | 5,058 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: hugging-doge
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9375
---
# hugging-doge
Autogenerated by H... |
vespa-engine/col-minilm | 0ca868b774f3a608777f70598f24027d54811a85 | 2021-05-20T08:59:29.000Z | [
"pytorch",
"bert",
"arxiv:2004.12832",
"transformers"
] | null | false | vespa-engine | null | vespa-engine/col-minilm | 80 | null | transformers | 5,059 | # MS Marco Ranking with ColBERT on Vespa.ai
Model is based on [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://arxiv.org/abs/2004.12832).
This BERT model is based on [cross-encoder/ms-marco-MiniLM-L-6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-... |
mmgyorke/vit-world-landmarks | 832c9992af16209cdb5e8a1142eb73021293ec06 | 2022-03-08T14:58:47.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | mmgyorke | null | mmgyorke/vit-world-landmarks | 80 | null | transformers | 5,060 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: vit-world-landmarks
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# vit-world-landmarks
Autogen... |
navteca/nli-deberta-v3-large | f0234a0e5be3aa6a94accf484286aff466e6470e | 2022-03-16T19:00:26.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"dataset:multi_nli",
"dataset:snli",
"transformers",
"microsoft/deberta-v3-large",
"license:apache-2.0",
"zero-shot-classification"
] | zero-shot-classification | false | navteca | null | navteca/nli-deberta-v3-large | 80 | 1 | transformers | 5,061 | ---
datasets:
- multi_nli
- snli
language: en
license: apache-2.0
metrics:
- accuracy
pipeline_tag: zero-shot-classification
tags:
- microsoft/deberta-v3-large
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.ne... |
uw-madison/nystromformer-1024 | 89bfdd8b6685661d79f1b460280f60ca7173b607 | 2022-03-26T14:58:18.000Z | [
"pytorch",
"nystromformer",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | uw-madison | null | uw-madison/nystromformer-1024 | 80 | null | transformers | 5,062 | Nystromformer for sequence length 1024 trained on WikiText-103 v1 for 150 epochs. |
JminJ/kcElectra_base_Bad_Sentence_Classifier | ac41bbb4ed53a44f5d716cb5beaeee1c5632e99e | 2022-04-11T01:49:19.000Z | [
"pytorch",
"electra",
"text-classification",
"arxiv:2003.10555",
"transformers"
] | text-classification | false | JminJ | null | JminJ/kcElectra_base_Bad_Sentence_Classifier | 80 | null | transformers | 5,063 | # Bad_text_classifier
## Model 소개
인터넷 상에 퍼져있는 여러 댓글, 채팅이 민감한 내용인지 아닌지를 판별하는 모델을 공개합니다. 해당 모델은 공개데이터를 사용해 label을 수정하고 데이터들을 합쳐 구성해 finetuning을 진행하였습니다. 해당 모델이 언제나 모든 문장을 정확히 판단이 가능한 것은 아니라는 점 양해해 주시면 감사드리겠습니다.
```
NOTE)
공개 데이터의 저작권 문제로 인해 모델 학습에 사용된 변형된 데이터는 공개 불가능하다는 점을 밝힙니다.
또한 해당 모델의 의견은 제 의견과 무관하다는 점을 미리 밝힙니다.
```
... |
hafidber/anomaly2 | 8733362e584dbb917fb65db84f2cc33c3e7d94f0 | 2022-04-07T16:22:25.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | hafidber | null | hafidber/anomaly2 | 80 | null | transformers | 5,064 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: anomaly2
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# anomaly2
Autogenerated by HuggingPics�... |
hafidber/anomaly | f996fe3712139370ea823c3ac96740391f6f9728 | 2022-04-17T12:14:15.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"model-index"
] | image-classification | false | hafidber | null | hafidber/anomaly | 80 | null | transformers | 5,065 | ---
tags:
- image-classification
- pytorch
metrics:
- accuracy
model-index:
- name: anomaly
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# anomaly
Anomaly classification
## Example Images
... |
arxyzan/data2vec-beit-base | 8f666c62d59212adbb2b20911a5d9e6264343507 | 2022-05-16T09:06:47.000Z | [
"pytorch",
"beit",
"feature-extraction",
"arxiv:2202.03555",
"transformers"
] | feature-extraction | false | arxyzan | null | arxyzan/data2vec-beit-base | 80 | null | transformers | 5,066 | A BEiT model trained using Data2Vec based on the paper [data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language](https://arxiv.org/abs/2202.03555).<br>
This model is provided here for [this repo](https://github.com/AryanShekarlaban/data2vec-pytorch) but was NOT trained using that codeb... |
dongxq/test_model | e142f2c3f941578bd9f05447f7529662486196eb | 2022-07-21T07:43:58.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"zh",
"transformers",
"summarization",
"autotrain_compatible"
] | summarization | false | dongxq | null | dongxq/test_model | 80 | null | transformers | 5,067 | ---
language: zh
tags:
- summarization
inference: True
---
Task: Summarization
## Usage
```python
from transformers import PegasusForConditionalGeneration,BertTokenizer
class PegasusTokenizer(BertTokenizer):
model_input_names = ["input_ids", "attention_mask"]
def __init__(self, **kwargs):
super().__i... |
wiselinjayajos/t5-end2end-questions-generation | b2fb779c3b8f9d2113b4ae226f2704b0bf30414e | 2022-06-24T08:04:22.000Z | [
"pytorch",
"t5",
"text2text-generation",
"dataset:wiselinjayajos/squad_modified_for_t5_qg",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | wiselinjayajos | null | wiselinjayajos/t5-end2end-questions-generation | 80 | null | transformers | 5,068 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wiselinjayajos/squad_modified_for_t5_qg
widget:
- text: "generate question: Python is developed by Guido Van Rossum and released in 1991.</s>"
model-index:
- name: t5-end2end-questions-generation
results: []
---
<!-- This model card has been generate... |
aalbertini1990/autotrain-first-test-html-1136241676 | 24efec92bdc59c02e955103e64cb3d2c1ebd2cc0 | 2022-07-15T17:59:11.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:aalbertini1990/autotrain-data-first-test-html",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | false | aalbertini1990 | null | aalbertini1990/autotrain-first-test-html-1136241676 | 80 | null | transformers | 5,069 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- aalbertini1990/autotrain-data-first-test-html
co2_eq_emissions: 684.7105644305452
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1136241676
- CO2 Emissions (in grams): 684.7105644305452
## Validation Met... |
priyankac/DialoGPT-medium-BaymaxBot | 6b379711a1c031f2e5c0dc330849838fc316b437 | 2022-07-29T15:03:33.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | priyankac | null | priyankac/DialoGPT-medium-BaymaxBot | 80 | null | transformers | 5,070 | ---
tags:
- conversational
---
#DialoGPT BaymaxBot |
AkshatSurolia/ViT-FaceMask-Finetuned | 5bf3e0383b71d0aab1cdf9156e0b6001ac70c17a | 2022-02-18T13:33:37.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:Face-Mask18K",
"transformers",
"license:apache-2.0"
] | image-classification | false | AkshatSurolia | null | AkshatSurolia/ViT-FaceMask-Finetuned | 79 | null | transformers | 5,071 | ---
license: apache-2.0
tags:
- image-classification
datasets:
- Face-Mask18K
---
# Vision Transformer (ViT) for Face Mask Detection
Vision Transformer (ViT) model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at resolution 224x224. It was first introduced ... |
Helsinki-NLP/opus-mt-ja-ar | c7f965141d5deebee1634136410ee3871af72eea | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"ar",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-ar | 79 | 1 | transformers | 5,072 | ---
language:
- ja
- ar
tags:
- translation
license: apache-2.0
---
### jpn-ara
* source group: Japanese
* target group: Arabic
* OPUS readme: [jpn-ara](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-ara/README.md)
* model: transformer-align
* source language(s): jpn_Hani jpn_Hira jp... |
Helsinki-NLP/opus-mt-ja-it | 3f22c1dc7990deab629e840b6c17d7b037398828 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"it",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-it | 79 | null | transformers | 5,073 | ---
language:
- ja
- it
tags:
- translation
license: apache-2.0
---
### jpn-ita
* source group: Japanese
* target group: Italian
* OPUS readme: [jpn-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-ita/README.md)
* model: transformer-align
* source language(s): jpn jpn_Hani jpn_Hi... |
KBLab/wav2vec2-large-xlsr-53-swedish | 1b654a832004c4885e361f21bff2fe3c23597f3e | 2021-07-05T14:33:04.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"sv-SE",
"dataset:common_voice",
"dataset:NST Swedish ASR Database",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | KBLab | null | KBLab/wav2vec2-large-xlsr-53-swedish | 79 | 1 | transformers | 5,074 | ---
language: sv-SE
datasets:
- common_voice
- NST Swedish ASR Database
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Swedish by KBLab
results:
- task:
name: Speech Recognition
type: automatic-sp... |
KoichiYasuoka/roberta-classical-chinese-base-char | 44cc49f98a2d917d6d7d8b4bc37274d48d6fc43a | 2021-10-30T00:37:55.000Z | [
"pytorch",
"roberta",
"fill-mask",
"lzh",
"transformers",
"classical chinese",
"literary chinese",
"ancient chinese",
"masked-lm",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | KoichiYasuoka | null | KoichiYasuoka/roberta-classical-chinese-base-char | 79 | null | transformers | 5,075 | ---
language:
- "lzh"
tags:
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "masked-lm"
license: "apache-2.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
widget:
- text: "孟子[MASK]梁惠王"
---
# roberta-classical-chinese-base-char
## Model Description
This is a RoBERTa model pre-trained on Classical C... |
Monsia/camembert-fr-covid-tweet-sentiment-classification | c84420561c5813052e8e78d236245abc93c74d77 | 2021-09-23T15:59:34.000Z | [
"pytorch",
"camembert",
"text-classification",
"fr",
"transformers",
"classification",
"license:apache-2.0"
] | text-classification | false | Monsia | null | Monsia/camembert-fr-covid-tweet-sentiment-classification | 79 | null | transformers | 5,076 | ---
language:
- fr
tags:
- classification
license: apache-2.0
metrics:
- accuracy
widget:
- text: "tchai on est morts. on va se faire vacciner et ils vont contrôler comme les marionnettes avec des fils. d'après les 'ont dit'..."
---
# camembert-fr-covid-tweet-sentiment-classification
This model is a fine-tune checkpoin... |
Tahsin-Mayeesha/wav2vec2-bn-300m | e10defcf153de4c09611db5204f9354b04644b38 | 2022-03-23T18:25:30.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"bn",
"dataset:openslr",
"dataset:SLR53",
"dataset:Harveenchadha/indic-text",
"transformers",
"hf-asr-leaderboard",
"openslr_SLR53",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | Tahsin-Mayeesha | null | Tahsin-Mayeesha/wav2vec2-bn-300m | 79 | 2 | transformers | 5,077 | ---
language:
- bn
license: apache-2.0
tags:
- automatic-speech-recognition
- hf-asr-leaderboard
- openslr_SLR53
- robust-speech-event
datasets:
- openslr
- SLR53
- Harveenchadha/indic-text
metrics:
- wer
- cer
model-index:
- name: Tahsin-Mayeesha/wav2vec2-bn-300m
results:
- task:
type: automatic-speech-recog... |
ajanco/greens | 9eb2f9b6205692343ccf7b4bd3030f72f20269b1 | 2021-12-12T22:39:52.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | ajanco | null | ajanco/greens | 79 | null | transformers | 5,078 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: greens
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7589285969734192
---
# greens
Autogenerated by H... |
dumitrescustefan/bert-base-romanian-ner | 7baf2afe672f696a0e96d8558e85ef01f672c7d4 | 2022-01-24T13:23:22.000Z | [
"pytorch",
"bert",
"token-classification",
"ro",
"dataset:ronec",
"arxiv:1909.01247",
"transformers",
"license:mit",
"autotrain_compatible"
] | token-classification | false | dumitrescustefan | null | dumitrescustefan/bert-base-romanian-ner | 79 | 1 | transformers | 5,079 | ---
language: ro
datasets:
- ronec
license: mit
---
# bert-base-romanian-ner
Updated: 21.01.2022
## Model description
**bert-base-romanian-ner** is a fine-tuned BERT model that is ready to use for **Named Entity Recognition** and achieves **state-of-the-art performance** for the NER task. It has been trained to reco... |
facebook/wav2vec2-large-xlsr-53-portuguese | c3b1a993605850e8f1e159ba57557925a05317c7 | 2021-07-06T03:05:04.000Z | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:common_voice",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | automatic-speech-recognition | false | facebook | null | facebook/wav2vec2-large-xlsr-53-portuguese | 79 | 1 | transformers | 5,080 | ---
language: pt
datasets:
- common_voice
tags:
- speech
- audio
- automatic-speech-recognition
license: apache-2.0
---
## Evaluation on Common Voice PT Test
```python
import torchaudio
from datasets import load_dataset, load_metric
from transformers import (
Wav2Vec2ForCTC,
Wav2Vec2Processor,
)
import torch
i... |
google/byt5-xxl | 3a43cc5c57a8f77dbffd92b701b605f034bb974e | 2022-05-27T15:07:06.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"multilingual",
"af",
"am",
"ar",
"az",
"be",
"bg",
"bn",
"ca",
"ceb",
"co",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fil",
"fr",
"fy",
"ga",
"gd",
"gl",
"gu",
"ha",
"... | text2text-generation | false | google | null | google/byt5-xxl | 79 | 4 | transformers | 5,081 | ---
language:
- multilingual
- af
- am
- ar
- az
- be
- bg
- bn
- ca
- ceb
- co
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fil
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- haw
- hi
- hmn
- ht
- hu
- hy
- ig
- is
- it
- iw
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lb
- lo
- lt
- lv
- mg
- mi
- mk
- ... |
jcblaise/roberta-tagalog-base | 7ab976a69b7cc338424ca08d228206e788756398 | 2021-11-12T03:25:36.000Z | [
"pytorch",
"tf",
"roberta",
"fill-mask",
"tl",
"transformers",
"tagalog",
"filipino",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | fill-mask | false | jcblaise | null | jcblaise/roberta-tagalog-base | 79 | null | transformers | 5,082 | ---
language: tl
tags:
- roberta
- tagalog
- filipino
license: cc-by-sa-4.0
inference: false
---
# RoBERTa Tagalog Base
Tagalog RoBERTa trained as an improvement over our previous Tagalog pretrained Transformers. Trained with TLUnified, a newer, larger, more topically-varied pretraining corpus for Filipino. This model... |
jjhoffstein/lotr | 431a24e9b00f95556fa241d0e27bd2bda7dfb184 | 2021-07-01T20:21:18.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | jjhoffstein | null | jjhoffstein/lotr | 79 | null | transformers | 5,083 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: lotr
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.4375
---
# lotr
Autogenerated by HuggingPics🤗🖼️
... |
mse30/bart-base-finetuned-arxiv | cfb4e9880a1783e8407b809ac818a59d2c20e391 | 2021-10-11T11:22:28.000Z | [
"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-arxiv | 79 | 1 | transformers | 5,084 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: bart-base-finetuned-arxiv
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_... |
nateraw/rare-puppers-123 | 55058e6f971f1dddb28d0bbda05ebdbd3848c0a3 | 2021-12-10T21:18:44.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | nateraw | null | nateraw/rare-puppers-123 | 79 | null | transformers | 5,085 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rare-puppers-123
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9701492786407471
---
# rare-puppers-123
... |
pranavpsv/gpt2-story-gen | 8ad52ce48b7143e09e6e524bb10c6fcdf727d9b5 | 2021-05-23T11:03:13.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | pranavpsv | null | pranavpsv/gpt2-story-gen | 79 | null | transformers | 5,086 | Entry not found |
surajp/RoBERTa-hindi-guj-san | 4464e6c2a7301ce0b58128b72c679bf6326a4b3b | 2021-05-20T22:02:11.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"hi",
"sa",
"gu",
"dataset:Wikipedia (Hindi, Sanskrit, Gujarati)",
"transformers",
"Indic",
"license:mit",
"autotrain_compatible"
] | fill-mask | false | surajp | null | surajp/RoBERTa-hindi-guj-san | 79 | null | transformers | 5,087 | ---
language:
- hi
- sa
- gu
tags:
- Indic
license: mit
datasets:
- Wikipedia (Hindi, Sanskrit, Gujarati)
metrics:
- perplexity
---
# RoBERTa-hindi-guj-san
## Model description
Multillingual RoBERTa like model trained on Wikipedia articles of Hindi, Sanskrit, Gujarati languages. The tokenizer was trained on combined... |
vanadhi/roberta-base-fiqa-flm-sq-flit | 63b86b4dbab4fc68f1e146b1bb0d46b695d1eed1 | 2021-12-25T18:36:54.000Z | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | question-answering | false | vanadhi | null | vanadhi/roberta-base-fiqa-flm-sq-flit | 79 | null | transformers | 5,088 | ---
tags:
- generated_from_trainer
model-index:
- name: roberta-base-fiqa-flm-sq-flit
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. -->
# roberta-base-fiqa-flm-sq-... |
vincentclaes/mit-indoor-scenes | 692e1df0648da10e2c9eb3c7f57444ef4da1d58e | 2022-05-30T20:16:07.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers",
"license:apache-2.0"
] | image-classification | false | vincentclaes | null | vincentclaes/mit-indoor-scenes | 79 | null | transformers | 5,089 |
---
license: apache-2.0
---
# MIT Indoor Scenes
Fine tune [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the data [MIT Indoor Scenes](https://www.kaggle.com/itsahmad/indoor-scenes-cvpr-2019)
|
ai4bharat/MultiIndicParaphraseGenerationSS | aaebef8c2f187ac7460cdddedb63f84481c2e3c0 | 2022-03-31T06:22:06.000Z | [
"pytorch",
"mbart",
"text2text-generation",
"as",
"bn",
"gu",
"hi",
"kn",
"ml",
"mr",
"or",
"pa",
"ta",
"te",
"dataset:ai4bharat/IndicParaphrase",
"arxiv:2203.05437",
"transformers",
"paraphrase-generation",
"multilingual",
"nlp",
"indicnlp",
"license:mit",
"autotrain_com... | text2text-generation | false | ai4bharat | null | ai4bharat/MultiIndicParaphraseGenerationSS | 79 | null | transformers | 5,090 | ---
tags:
- paraphrase-generation
- multilingual
- nlp
- indicnlp
datasets:
- ai4bharat/IndicParaphrase
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
license:
- mit
---
# MultiIndicParaphraseGenerationSS
This repository contains the [IndicBARTSS](https://huggingface.co... |
osanseviero/llama-or-potato | de1c463255b51e735e09bb1c3ce2c9720e15a1b6 | 2022-04-01T09:45:26.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"llama-leaderboard",
"model-index"
] | image-classification | false | osanseviero | null | osanseviero/llama-or-potato | 79 | null | transformers | 5,091 | ---
tags:
- image-classification
- pytorch
- huggingpics
- llama-leaderboard
metrics:
- accuracy
model-index:
- name: llama-or-potato
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 1.0
---
# llama-or-pota... |
johnnydevriese/vit-airplanes | 7208ffe9964d46a29d86a931d6b939f80bf3fccd | 2022-04-08T17:04:33.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | johnnydevriese | null | johnnydevriese/vit-airplanes | 79 | null | transformers | 5,092 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vit-airplanes
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
... |
whatAboutThis/swin-tiny-patch4-window7-224-finetuned-eurosat | f3e5bdf98f99ac9fee2a3d8ca0f0fa59c61c8a9e | 2022-05-10T20:17:47.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"transformers"
] | image-classification | false | whatAboutThis | null | whatAboutThis/swin-tiny-patch4-window7-224-finetuned-eurosat | 79 | null | transformers | 5,093 | Entry not found |
guhuawuli/swin-tiny-patch4-window7-224-finetuned-eurosat | d0c534901fc480db34d9b4ab0a76baec1d9162e4 | 2022-05-11T13:01:51.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | guhuawuli | null | guhuawuli/swin-tiny-patch4-window7-224-finetuned-eurosat | 79 | null | transformers | 5,094 | ---
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
... |
SimonZvara/Memes-CS_1.0 | c082f3c7c8f06f656d20510d9e8349fe30fe3fd4 | 2022-05-18T21:48:22.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | SimonZvara | null | SimonZvara/Memes-CS_1.0 | 79 | null | transformers | 5,095 | Model used by Memes-CS (Metric for Evaluating Model Efficiency in Summarization).
Part of my bachelor's thesis.
Šimon Zvára |
Jazzweller/swin-tiny-patch4-window7-224-finetuned-eurosat | 2041f1adc1114a278d85f42e5bdccfca49eba274 | 2022-05-28T20:33:02.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | Jazzweller | null | Jazzweller/swin-tiny-patch4-window7-224-finetuned-eurosat | 79 | null | transformers | 5,096 | ---
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
... |
brjezierski/german-gpt2-easy | 6b07bffc62b4dacfe9167a6ae678a1d7c0b69e36 | 2022-06-30T14:08:20.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | brjezierski | null | brjezierski/german-gpt2-easy | 79 | null | transformers | 5,097 | Entry not found |
Yehor/wav2vec2-xls-r-base-uk-with-cv-lm | 870a12c9507c829b90cfc5d7a89eabb5d108c28c | 2022-07-30T06:59:54.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"uk",
"dataset:mozilla-foundation/common_voice_10_0",
"transformers",
"license:cc-by-nc-sa-4.0"
] | automatic-speech-recognition | false | Yehor | null | Yehor/wav2vec2-xls-r-base-uk-with-cv-lm | 79 | null | transformers | 5,098 | ---
language:
- uk
license: "cc-by-nc-sa-4.0"
datasets:
- mozilla-foundation/common_voice_10_0
---
🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech_recognition_uk
⭐ See other Ukrainian models - https://github.com/egorsmkv/speech-recognition-uk
This model was trained using the base model http... |
allenai/led-base-16384-ms2 | 92d4b406bf677c75df3bef90ccd5ca2e1c28d679 | 2022-07-27T18:04:42.000Z | [
"pytorch",
"led",
"text2text-generation",
"dataset:allenai/mslr2022",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | allenai | null | allenai/led-base-16384-ms2 | 79 | 1 | transformers | 5,099 | ---
tags:
- generated_from_trainer
datasets:
- allenai/mslr2022
model-index:
- name: baseline
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. -->
# Overview
This mo... |
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