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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
hackathon-pln-es/t5-small-finetuned-spanish-to-quechua | 1a1c1a24c23a9b4cff2444718dcbc958875018cb | 2022-04-03T05:42:56.000Z | [
"pytorch",
"t5",
"text2text-generation",
"es",
"qu",
"transformers",
"quechua",
"translation",
"spanish",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | hackathon-pln-es | null | hackathon-pln-es/t5-small-finetuned-spanish-to-quechua | 90 | 4 | transformers | 4,800 | ---
language:
- es
- qu
tags:
- quechua
- translation
- spanish
license: apache-2.0
metrics:
- bleu
- sacrebleu
widget:
- text: "Dios ama a los hombres"
- text: "A pesar de todo, soy feliz"
- text: "¿Qué harán allí?"
- text: "Debes aprender a respetar"
---
# Spanish to Quechua translator
This model is a finetune... |
ccdv/lsg-bart-base-16384-pubmed | ee321b6636965d14801b58b61362a34b5704a23c | 2022-07-25T05:29:10.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:scientific_papers",
"transformers",
"summarization",
"model-index",
"autotrain_compatible"
] | summarization | false | ccdv | null | ccdv/lsg-bart-base-16384-pubmed | 90 | 3 | transformers | 4,801 | ---
language:
- en
tags:
- summarization
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: ccdv/lsg-bart-base-16384-pubmed
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... |
sanjay-m1/parrot-adequacy-on-BART | 0514f368694920fc841582af98ed94f720a00df2 | 2022-05-21T17:37:29.000Z | [
"pytorch",
"bart",
"transformers"
] | null | false | sanjay-m1 | null | sanjay-m1/parrot-adequacy-on-BART | 90 | null | transformers | 4,802 | # Parrot
THIS IS AN ANCILLARY MODEL FOR PARROT PARAPHRASER
## 1. What is Parrot?
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model. Please refer to the [github page](https://github.com/PrithivirajD... |
eunsour/en-ko-transliterator | 169f2b5772f9347985d0a7ab462685c801b8cbfe | 2022-06-28T14:32:25.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | eunsour | null | eunsour/en-ko-transliterator | 90 | 0 | transformers | 4,803 | ```
!pip install simpletransformers
from simpletransformers.t5 import T5Model
model = T5Model("mt5", "eunsour/en-ko-transliterator", use_cuda=False)
print(model.predict(["transformer"]))
print(model.predict(["attention"]))
``` |
JulesBelveze/t5-small-headline-generator | 58ef632459769780866fa6d16a9cfbc69add8cb0 | 2022-07-01T05:17:57.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:JulesBelveze/tldr_news",
"transformers",
"summarization",
"headline-generation",
"text-generation",
"autotrain_compatible"
] | summarization | false | JulesBelveze | null | JulesBelveze/t5-small-headline-generator | 90 | 2 | transformers | 4,804 | ---
language:
- en
tags:
- summarization
- headline-generation
- text-generation
datasets:
- JulesBelveze/tldr_news
metrics:
- rouge1
- rouge2
- rougeL
- rougeLsum
---
# t5-small for headline generation
This model is a [t5-small](https://huggingface.co/t5-small) fine-tuned for headline generation using
the [JulesBel... |
Amrrs/indian-foods | f17394f1fb1e91fc497c5124805a0ca7db91dc03 | 2021-07-20T10:20:55.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | Amrrs | null | Amrrs/indian-foods | 89 | 1 | transformers | 4,805 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: indian-foods
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9285714030265808
---
# indian-foods
Autoge... |
DeepChem/SmilesTokenizer_PubChem_1M | 4922f620c0488ad0362ba89430f8c96041072c29 | 2021-05-31T20:54:05.000Z | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | false | DeepChem | null | DeepChem/SmilesTokenizer_PubChem_1M | 89 | null | transformers | 4,806 | RoBERTa model trained on 1M SMILES from PubChem 77M set in MoleculeNet. Uses Smiles-Tokenizer |
Helsinki-NLP/opus-mt-de-ZH | 93d4bc065a572a35ab1f1110ffeccc9740444a42 | 2021-09-09T21:30:07.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"zh",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-ZH | 89 | 1 | transformers | 4,807 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-de-ZH
* source languages: de
* target languages: cmn,cn,yue,ze_zh,zh_cn,zh_CN,zh_HK,zh_tw,zh_TW,zh_yue,zhs,zht,zh
* OPUS readme: [de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/... |
Helsinki-NLP/opus-mt-es-vi | b3b69971697a56c967a303713e0f4dcd06256311 | 2021-01-18T08:29:49.000Z | [
"pytorch",
"marian",
"text2text-generation",
"es",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-es-vi | 89 | null | transformers | 4,808 | ---
language:
- es
- vi
tags:
- translation
license: apache-2.0
---
### spa-vie
* source group: Spanish
* target group: Vietnamese
* OPUS readme: [spa-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-vie/README.md)
* model: transformer-align
* source language(s): spa
* target lang... |
MKaan/multilingual-cpv-sector-classifier | 593b7b5901a38e28cdf27fe3381ae96dc172415e | 2021-11-28T13:09:32.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers",
"eu",
"public procurement",
"cpv",
"sector",
"multilingual",
"license:apache-2.0"
] | text-classification | false | MKaan | null | MKaan/multilingual-cpv-sector-classifier | 89 | 3 | transformers | 4,809 | ---
license: apache-2.0
tags:
- eu
- public procurement
- cpv
- sector
- multilingual
- transformers
- text-classification
widget:
- text: "Oppegård municipality, hereafter called the contracting authority, intends to enter into a framework agreement with one supplier for the procurement of fresh bread and bakery produ... |
NDugar/v3-Large-mnli | 291554748314581adf4398af85d52b5f14f7f70e | 2021-12-26T15:27:41.000Z | [
"pytorch",
"deberta-v2",
"text-classification",
"en",
"transformers",
"deberta-v1",
"deberta-mnli",
"license:mit",
"zero-shot-classification"
] | zero-shot-classification | false | NDugar | null | NDugar/v3-Large-mnli | 89 | 1 | transformers | 4,810 | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the GLUE MNLI... |
PaulLerner/dpr_context_encoder_triviaqa_without_viquae | d1c83af9b648a6dbe234dfb51c4713ecceed2d9f | 2022-02-18T13:58:18.000Z | [
"pytorch",
"dpr",
"transformers"
] | null | false | PaulLerner | null | PaulLerner/dpr_context_encoder_triviaqa_without_viquae | 89 | null | transformers | 4,811 | Entry not found |
cosmoquester/bart-ko-small | 32c6ec5844197a774d6460e7fc83812af9dc24e3 | 2021-08-28T05:09:54.000Z | [
"pytorch",
"tf",
"bart",
"text2text-generation",
"ko",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | cosmoquester | null | cosmoquester/bart-ko-small | 89 | null | transformers | 4,812 | ---
language: ko
---
# Pretrained BART in Korean
This is pretrained BART model with multiple Korean Datasets.
I used multiple datasets for generalizing the model for both colloquial and written texts.
The training is supported by [TPU Research Cloud](https://sites.research.google/trc/) program.
The script which is... |
mrm8488/deberta-v3-small-finetuned-sst2 | 94d075b4095d80dde2c23ad513ebcac7bfe7f0ad | 2021-11-21T19:17:56.000Z | [
"pytorch",
"tensorboard",
"deberta-v2",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"deberta-v3",
"license:mit",
"model-index"
] | text-classification | false | mrm8488 | null | mrm8488/deberta-v3-small-finetuned-sst2 | 89 | null | transformers | 4,813 | ---
language:
- en
license: mit
tags:
- generated_from_trainer
- deberta-v3
datasets:
- glue
metrics:
- accuracy
model-index:
- name: deberta-v3-small
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glue
args: sst2
metrics:
... |
salesken/paraphrase_generation | 1141e8ba54581a8130c4adcc407ae85525d1cf4f | 2021-05-23T12:33:04.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"salesken",
"license:apache-2.0"
] | text-generation | false | salesken | null | salesken/paraphrase_generation | 89 | 1 | transformers | 4,814 | ---
language: en
thumbnail: https://salesken.ai/assets/images/logo.png
license: apache-2.0
inference: false
widget:
- text: "every moment is a fresh beginning"
tags: salesken
---
Use this model to generate variations to augment the training data used for NLU systems.
```python
from transformers import AutoTokenize... |
timm/vit_huge_patch14_224_in21k | bbf572e74b9cf2a10daa9461505cb506c9189c4a | 2021-03-18T10:58:13.000Z | [
"pytorch",
"dataset:imagenet_21k",
"timm",
"image-classification",
"vision-transformer",
"license:apache-2.0"
] | image-classification | false | timm | null | timm/vit_huge_patch14_224_in21k | 89 | null | timm | 4,815 | ---
tags:
- image-classification
- timm
- vision-transformer
license: apache-2.0
datasets:
- imagenet_21k
inference: false
---
# ViT-H/14 (ImageNet-21k)
...
|
yongzx/gpt2-finetuned-oscar-fr-ori-tok | b3f3f7e2dc1729199e44424c6b7edc1aaafa18f6 | 2021-12-09T06:37:06.000Z | [
"pytorch",
"gpt2",
"text-generation",
"fr",
"dataset:oscar",
"transformers",
"license:mit"
] | text-generation | false | yongzx | null | yongzx/gpt2-finetuned-oscar-fr-ori-tok | 89 | null | transformers | 4,816 | ---
language:
- fr
tags:
- text-generation
license: mit
datasets:
- oscar
widget:
- text: "Je suis ravi de vous "
---
# GPT-2 finetuned on French Dataset
### Tokenizer
We use GPT-2 tokenizer.
### Model
We finetuned the `wte` and `wpe` layers of GPT-2 (while freezing the parameters of all other layers) on OSCAR's ... |
ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_essays_TEST_editorials_05_03_2022-06_21_38 | 328afb20b84511cb9c350d495c6a3a90922aefc1 | 2022-03-05T05:24:04.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ali2066 | null | ali2066/bert-base-uncased_token_itr0_0.0001_TRAIN_essays_TEST_editorials_05_03_2022-06_21_38 | 89 | null | transformers | 4,817 | Entry not found |
jkhan447/sentiment-model-sample-27go-emotion | 2e63119a9d2b37e5e054e903f62cded65ee34a70 | 2022-04-01T08:13:56.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:go_emotions",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | jkhan447 | null | jkhan447/sentiment-model-sample-27go-emotion | 89 | null | transformers | 4,818 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- accuracy
model-index:
- name: sentiment-model-sample-27go-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: go_emotions
args: simpli... |
ismail-lucifer011/autotrain-company_all-903429548 | acbdc6779e48dfde49f2ba77d6f2cfb431333d16 | 2022-05-24T14:24:20.000Z | [
"pytorch",
"distilbert",
"token-classification",
"en",
"dataset:ismail-lucifer011/autotrain-data-company_all",
"transformers",
"autotrain",
"co2_eq_emissions",
"autotrain_compatible"
] | token-classification | false | ismail-lucifer011 | null | ismail-lucifer011/autotrain-company_all-903429548 | 89 | null | transformers | 4,819 | ---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ismail-lucifer011/autotrain-data-company_all
co2_eq_emissions: 0.848790823793881
---
# Model Trained Using AutoTrain
- Problem type: Entity Extraction
- Model ID: 903429548
- CO2 Emissions (in grams): 0.848790823793881
## Validation M... |
Genario/multilingual_paraphrase | 40fa64fac60a68006923e19daefa6545b780888c | 2022-06-27T13:01:00.000Z | [
"pytorch",
"tf",
"bert",
"feature-extraction",
"multilingual",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | false | Genario | null | Genario/multilingual_paraphrase | 89 | null | sentence-transformers | 4,820 | ---
pipeline_tag: feature-extraction
language: multilingual
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & ... |
nielsr/convnext-tiny-maskrcnn | 4e675c60d14587de898a2803cc34dc733f9a4899 | 2022-06-28T10:05:05.000Z | [
"pytorch",
"convnext_maskrcnn",
"transformers"
] | null | false | nielsr | null | nielsr/convnext-tiny-maskrcnn | 89 | null | transformers | 4,821 | Entry not found |
throwaway112358112358/DialoGPT-medium-script | 890ae93de34b8c42ca3e5b21a3ef09ca410f4fd0 | 2022-07-22T06:23:55.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | throwaway112358112358 | null | throwaway112358112358/DialoGPT-medium-script | 89 | null | transformers | 4,822 | ---
tags:
- conversational
---
# America DialoGPT Model |
Helsinki-NLP/opus-mt-af-es | 2b07ca080f32eb33642e2da486f8e5846f1bd7b7 | 2021-01-18T07:46:14.000Z | [
"pytorch",
"marian",
"text2text-generation",
"af",
"es",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-af-es | 88 | null | transformers | 4,823 | ---
language:
- af
- es
tags:
- translation
license: apache-2.0
---
### afr-spa
* source group: Afrikaans
* target group: Spanish
* OPUS readme: [afr-spa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afr-spa/README.md)
* model: transformer-align
* source language(s): afr
* target langu... |
Helsinki-NLP/opus-mt-ar-pl | 623776f6e081085cf6c215c9fd91326fbf80e090 | 2021-01-18T07:47:35.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ar",
"pl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ar-pl | 88 | null | transformers | 4,824 | ---
language:
- ar
- pl
tags:
- translation
license: apache-2.0
---
### ara-pol
* source group: Arabic
* target group: Polish
* OPUS readme: [ara-pol](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-pol/README.md)
* model: transformer
* source language(s): ara arz
* target language(s)... |
Ivo/emscad-skill-extraction-token-classification | e8aea8bda132c66d6408535e2d24f75e021a3006 | 2021-06-15T09:37:47.000Z | [
"pytorch",
"tf",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | Ivo | null | Ivo/emscad-skill-extraction-token-classification | 88 | null | transformers | 4,825 | Entry not found |
dbernsohn/roberta-java | 17434de4294ec97090e7a2286d5b395013b1bfe1 | 2021-05-20T15:54:29.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"Java",
"dataset:code_search_net",
"arxiv:1907.11692",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbernsohn | null | dbernsohn/roberta-java | 88 | 1 | transformers | 4,826 | # roberta-java
---
language: Java
datasets:
- code_search_net
---
This is a [roberta](https://arxiv.org/pdf/1907.11692.pdf) pre-trained version on the [CodeSearchNet dataset](https://github.com/github/CodeSearchNet) for **Java** Mask Language Model mission.
To load the model:
(necessary packages: !pip install transfo... |
flax-community/pino-bigbird-roberta-base | 81688aa15c56f034bdb694e75f526c884231de6d | 2022-01-13T15:29:26.000Z | [
"pytorch",
"jax",
"tensorboard",
"big_bird",
"fill-mask",
"nl",
"dataset:mC4",
"dataset:Dutch_news",
"arxiv:2007.14062",
"transformers",
"autotrain_compatible"
] | fill-mask | false | flax-community | null | flax-community/pino-bigbird-roberta-base | 88 | 1 | transformers | 4,827 | ---
language: nl
datasets:
- mC4
- Dutch_news
---
# Pino (Dutch BigBird) base model
Created by [Dat Nguyen](https://www.linkedin.com/in/dat-nguyen-49a641138/) & [Yeb Havinga](https://www.linkedin.com/in/yeb-havinga-86530825/) during the [Hugging Face community week](https://discuss.huggingface.co/t/open-to-the-commun... |
gatecitypreservation/architectural_styles | ae57ad5ef7d339c28bee56b608e4e8830284c8f3 | 2022-01-07T18:41:50.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | gatecitypreservation | null | gatecitypreservation/architectural_styles | 88 | 1 | transformers | 4,828 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: architectural_styles
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7796609997749329
---
### What style ... |
google/bert_uncased_L-2_H-512_A-8 | 880c57fdc84683dd9ce13a2fdbdd454abc488fb6 | 2021-05-19T17:29:08.000Z | [
"pytorch",
"jax",
"bert",
"arxiv:1908.08962",
"transformers",
"license:apache-2.0"
] | null | false | google | null | google/bert_uncased_L-2_H-512_A-8 | 88 | null | transformers | 4,829 | ---
thumbnail: https://huggingface.co/front/thumbnails/google.png
license: apache-2.0
---
BERT Miniatures
===
This is the set of 24 BERT models referenced in [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962) (English only, uncased, trained with Word... |
google/tapas-small-finetuned-tabfact | 2d1b432ff29227fabbfab71456ddec10581a163f | 2021-11-29T13:07:47.000Z | [
"pytorch",
"tf",
"tapas",
"text-classification",
"en",
"dataset:tab_fact",
"arxiv:2010.00571",
"arxiv:2004.02349",
"transformers",
"sequence-classification",
"license:apache-2.0"
] | text-classification | false | google | null | google/tapas-small-finetuned-tabfact | 88 | null | transformers | 4,830 | ---
language: en
tags:
- tapas
- sequence-classification
license: apache-2.0
datasets:
- tab_fact
---
# TAPAS small model fine-tuned on Tabular Fact Checking (TabFact)
This model has 2 versions which can be used. The latest version, which is the default one, corresponds to the `tapas_tabfact_inter_masklm_small_rese... |
ibombonato/swin-age-classifier | 5ebf0a390d42254891441ddc0ba9a72564aaa1eb | 2022-02-11T21:42:47.000Z | [
"pytorch",
"tensorboard",
"swin",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | ibombonato | null | ibombonato/swin-age-classifier | 88 | null | transformers | 4,831 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: swin-age-classifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.8174999952316284
---
# swin-age-class... |
mrm8488/gpt2-finetuned-recipes-cooking | b4f72aae501e00b4a1ba022ef93cb5269ed9eaf7 | 2021-05-23T10:24:14.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers"
] | text-generation | false | mrm8488 | null | mrm8488/gpt2-finetuned-recipes-cooking | 88 | null | transformers | 4,832 | ---
language: en
thumbnail:
widget:
- text: "HuggingFace Cake:"
---
|
navteca/roberta-large-squad2 | 2434d399f7a25d47d72c7080d0e3905e6cd4bceb | 2021-04-06T16:31:09.000Z | [
"pytorch",
"jax",
"roberta",
"question-answering",
"en",
"dataset:squad_v2",
"transformers",
"license:mit",
"autotrain_compatible"
] | question-answering | false | navteca | null | navteca/roberta-large-squad2 | 88 | null | transformers | 4,833 | ---
datasets:
- squad_v2
language: en
license: mit
pipeline_tag: question-answering
tags:
- roberta
- question-answering
---
# Roberta large model for QA (SQuAD 2.0)
This model uses [roberta-large](https://huggingface.co/roberta-large).
## Training Data
The models have been trained on the [SQuAD 2.0](https://rajpurka... |
prajjwal1/roberta-base-mnli | de6e05e0d9382d5344202c667368602666c8e1b2 | 2021-05-20T19:31:02.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | prajjwal1 | null | prajjwal1/roberta-base-mnli | 88 | null | transformers | 4,834 | Roberta-base trained on MNLI.
| Task | Accuracy |
|---------|----------|
| MNLI | 86.32 |
| MNLI-mm | 86.43 |
You can also check out:
- `prajjwal1/roberta-base-mnli`
- `prajjwal1/roberta-large-mnli`
- `prajjwal1/albert-base-v2-mnli`
- `prajjwal1/albert-base-v1-mnli`
- `prajjwal1/albert-large-v2-mnli`
[@... |
sagorsarker/codeswitch-hineng-pos-lince | 2482a85d58bd6ac78a8d90f82bbcd600584cdd92 | 2021-05-19T01:06:07.000Z | [
"pytorch",
"jax",
"bert",
"token-classification",
"hi",
"en",
"dataset:lince",
"transformers",
"codeswitching",
"hindi-english",
"pos",
"license:mit",
"autotrain_compatible"
] | token-classification | false | sagorsarker | null | sagorsarker/codeswitch-hineng-pos-lince | 88 | null | transformers | 4,835 | ---
language:
- hi
- en
datasets:
- lince
license: mit
tags:
- codeswitching
- hindi-english
- pos
---
# codeswitch-hineng-pos-lince
This is a pretrained model for **Part of Speech Tagging** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
This model is trained for this below rep... |
tanmaylaud/wav2vec2-large-xlsr-hindi-marathi | 269a6b04018f4d7a6740403b27ed58386bd77788 | 2021-04-19T18:40:07.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"mr",
"hi",
"dataset:openslr",
"dataset:interspeech_2021_asr",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"hindi",
"marathi",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | tanmaylaud | null | tanmaylaud/wav2vec2-large-xlsr-hindi-marathi | 88 | null | transformers | 4,836 | ---
language: [mr,hi]
datasets:
- openslr
- interspeech_2021_asr
metrics:
- wer
tags:
- audio
- automatic-speech-recognition
- speech
- xlsr-fine-tuning-week
- hindi
- marathi
license: apache-2.0
model-index:
- name: XLSR Wav2Vec2 Large 53 Hindi-Marathi by Tanmay Laud
results:
- task:
name: Speech Recognitio... |
facebook/maskformer-swin-large-coco | 194762ea9a98ec6d18abed4023aa346dcf1722c3 | 2022-04-04T16:02:13.000Z | [
"pytorch",
"maskformer",
"dataset:coco",
"arxiv:2107.06278",
"transformers",
"vision",
"image-segmentatiom",
"license:apache-2.0"
] | null | false | facebook | null | facebook/maskformer-swin-large-coco | 88 | null | transformers | 4,837 | ---
license: apache-2.0
tags:
- vision
- image-segmentatiom
datasets:
- coco
---
# Mask
Mask model trained on coco. It was introduced in the paper [Per-Pixel Classification is Not All You Need for Semantic Segmentation](https://arxiv.org/abs/2107.06278) and first released in [this repository](https://github.com/f... |
cometrain/stocks-news-t5 | c201c487d5821a136c7f4422b99d04d2abf68344 | 2022-04-14T10:08:16.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:financial-sentiment-analysis",
"transformers",
"Cometrain AutoCode",
"Cometrain AlphaML",
"autotrain_compatible"
] | text2text-generation | false | cometrain | null | cometrain/stocks-news-t5 | 88 | null | transformers | 4,838 | ---
language:
- en
tags:
- Cometrain AutoCode
- Cometrain AlphaML
datasets:
- financial-sentiment-analysis
widget:
- text: "April 14 (Reuters) - Rio Tinto (RIO.AX), one of the largest Australian mining companies, on Thursday confirmed its exit from the state mining lobby group after raising concerns that its policy ... |
MiBo/SegBert | 67517fe0e778a6f0a0f332725d8d784bae4ee930 | 2022-05-23T12:12:33.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | MiBo | null | MiBo/SegBert | 88 | null | transformers | 4,839 | Entry not found |
PrimeQA/tydiqa-boolean-answer-classifier | 548277c8c7a0c04468b1f99841364b731393cfe2 | 2022-06-28T19:52:14.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"arxiv:2112.07772",
"arxiv:2206.08441",
"transformers",
"license:apache-2.0"
] | text-classification | false | PrimeQA | null | PrimeQA/tydiqa-boolean-answer-classifier | 88 | null | transformers | 4,840 | ---
license: apache-2.0
---
## Model description
An answer classification model for boolean questions based on XLM-RoBERTa.
The answer classifier takes as input a boolean question and a passage, and returns a label (yes, no-answer, no).
The model was initialized with [xlm-roberta-large](https://huggingface.co/xlm... |
ml6team/keyphrase-extraction-kbir-openkp | f17ec53f7000ea5f7d760ef6bb49efe5e2af49ca | 2022-06-17T06:45:06.000Z | [
"pytorch",
"roberta",
"token-classification",
"en",
"dataset:midas/openkp",
"arxiv:2112.08547",
"arxiv:1911.02671",
"transformers",
"keyphrase-extraction",
"license:mit",
"model-index",
"autotrain_compatible"
] | token-classification | false | ml6team | null | ml6team/keyphrase-extraction-kbir-openkp | 88 | null | transformers | 4,841 | ---
language: en
license: mit
tags:
- keyphrase-extraction
datasets:
- midas/openkp
metrics:
- seqeval
widget:
- text: "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document.
Thanks to these keyphrases humans can understand the content of a text very quickly a... |
hakurei/litv2-6B-rev3 | b3149de232b8f398645015eaef23c2dd886f244b | 2022-06-17T04:54:20.000Z | [
"pytorch",
"gptj",
"text-generation",
"transformers"
] | text-generation | false | hakurei | null | hakurei/litv2-6B-rev3 | 88 | null | transformers | 4,842 | https://wandb.ai/haruu/mesh-transformer-jax/runs/1iae931p?workspace=user-haruu |
davidcechak/DNADebertaK8 | e34c774d03fc1c65d877d21134f86a5c58ac35e9 | 2022-07-05T22:54:48.000Z | [
"pytorch",
"tensorboard",
"deberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | davidcechak | null | davidcechak/DNADebertaK8 | 88 | null | transformers | 4,843 | Entry not found |
CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment | a5482ef3f4cf508d383ef4a3cc7ce40cfa12722b | 2021-10-17T11:15:12.000Z | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | false | CAMeL-Lab | null | CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment | 87 | 2 | transformers | 4,844 | ---
language:
- ar
license: apache-2.0
widget:
- text: "أنا بخير"
---
# CAMeLBERT-CA SA Model
## Model description
**CAMeLBERT-CA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Classical Arabic (CA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
Fo... |
Helsinki-NLP/opus-mt-fr-pl | e7d23016ef0cf42510b2a7701e36b8b08b96399c | 2021-09-09T21:56:11.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fr",
"pl",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-fr-pl | 87 | null | transformers | 4,845 | ---
tags:
- translation
license: apache-2.0
---
### opus-mt-fr-pl
* source languages: fr
* target languages: pl
* OPUS readme: [fr-pl](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fr-pl/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... |
Helsinki-NLP/opus-mt-ja-pt | 654bbe699ed24805d8f5155246b278b3fa65acb9 | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"pt",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-pt | 87 | null | transformers | 4,846 | ---
language:
- ja
- pt
tags:
- translation
license: apache-2.0
---
### jpn-por
* source group: Japanese
* target group: Portuguese
* OPUS readme: [jpn-por](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-por/README.md)
* model: transformer-align
* source language(s): jpn jpn_Hani jpn... |
NLP4H/ms_bert | 7883a03983cc71f12af68e838fad140865cbf97f | 2021-05-18T21:46:48.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | NLP4H | null | NLP4H/ms_bert | 87 | null | transformers | 4,847 | # MS-BERT
## Introduction
This repository provides codes and models of MS-BERT.
MS-BERT was pre-trained on notes from neurological examination for Multiple Sclerosis (MS) patients at St. Michael's Hospital in Toronto, Canada.
## Data
The dataset contained approximately 75,000 clinical notes, for about 5000 patients... |
NbAiLab/nb-bert-base-ner | b925de07fe9e9dc55c20cd72364b791aef42e2d0 | 2022-06-01T10:49:24.000Z | [
"pytorch",
"bert",
"token-classification",
"no",
"dataset:norne",
"transformers",
"norwegian",
"ner",
"license:cc-by-4.0",
"autotrain_compatible"
] | token-classification | false | NbAiLab | null | NbAiLab/nb-bert-base-ner | 87 | null | transformers | 4,848 | ---
language: no
license: cc-by-4.0
tags:
- norwegian
- bert
- ner
thumbnail: nblogo_3.png
pipeline_tag: token-classification
datasets:
- norne
inference:
parameters:
aggregation_strategy: "first"
widget:
- text: Trond Giske har bekreftet på spørsmål fra Adresseavisen at Hansen leide et rom i hans leilighet i Tro... |
Saz/DialoGPT-small-saz | 10167fd59643d1389903b0f470c64bae721de24c | 2021-10-08T06:08:56.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | Saz | null | Saz/DialoGPT-small-saz | 87 | null | transformers | 4,849 | ---
tags:
- conversational
---
# Saz DialoGPT Model |
UBC-NLP/AraT5-tweet-base | 8926762f3fdf3661c8b632f368e1a5f5b4c5a1ab | 2022-05-26T18:26:55.000Z | [
"pytorch",
"tf",
"t5",
"ar",
"transformers",
"Arabic T5",
"MSA",
"Twitter",
"Arabic Dialect",
"Arabic Machine Translation",
"Arabic Text Summarization",
"Arabic News Title and Question Generation",
"Arabic Paraphrasing and Transliteration",
"Arabic Code-Switched Translation"
] | null | false | UBC-NLP | null | UBC-NLP/AraT5-tweet-base | 87 | 1 | transformers | 4,850 | ---
language:
- ar
tags:
- Arabic T5
- MSA
- Twitter
- Arabic Dialect
- Arabic Machine Translation
- Arabic Text Summarization
- Arabic News Title and Question Generation
- Arabic Paraphrasing and Transliteration
- Arabic Code-Switched Translation
---
# AraT5-base
# AraT5: Text-to-Text Transformers... |
facebook/detr-resnet-50-dc5 | e3ea9b76022e0df3be936441d20ee5470886f557 | 2022-06-27T08:36:56.000Z | [
"pytorch",
"detr",
"object-detection",
"dataset:coco",
"arxiv:2005.12872",
"transformers",
"vision",
"license:apache-2.0"
] | object-detection | false | facebook | null | facebook/detr-resnet-50-dc5 | 87 | 1 | transformers | 4,851 | ---
license: apache-2.0
tags:
- object-detection
- vision
datasets:
- coco
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- s... |
franklu/pubmed_bert_squadv2 | 3abeb3561a41c7960a4b24b4a9629d06d9f2254b | 2021-07-09T05:25:26.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | franklu | null | franklu/pubmed_bert_squadv2 | 87 | null | transformers | 4,852 | **[`microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext`](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext)** fine-tuned on **[`SQuAD V2`](https://rajpurkar.github.io/SQuAD-explorer/)** using **[`run_qa.py`](https://github.com/huggingface/transformers/blob/master/examples/p... |
fspanda/Medical-Bio-BERT2 | f3fe25c06099883d3116d1395afa8df37fa0cb93 | 2021-05-19T16:57:41.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | fspanda | null | fspanda/Medical-Bio-BERT2 | 87 | null | transformers | 4,853 | Entry not found |
google/t5-large-ssm | 0b0101c39a17cb38660e671692bdd892ba5d352d | 2021-06-23T01:49:33.000Z | [
"pytorch",
"tf",
"jax",
"t5",
"text2text-generation",
"en",
"dataset:c4",
"dataset:wikipedia",
"arxiv:2002.08909",
"arxiv:1910.10683",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | google | null | google/t5-large-ssm | 87 | 1 | transformers | 4,854 | ---
language: en
datasets:
- c4
- wikipedia
license: apache-2.0
---
[Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) for **Closed Book Question Answering**.
The model was pre-trained using T5's denoising objective on [C4](https://huggingface.co/datasets/c4) and subsequently a... |
illuin/camembert-base-fquad | 8fea54f3caae6eef44ee1d1c52026ac48752a6c0 | 2020-12-11T21:45:27.000Z | [
"pytorch",
"camembert",
"question-answering",
"fr",
"dataset:fquad",
"transformers",
"license:gpl-3.0",
"autotrain_compatible"
] | question-answering | false | illuin | null | illuin/camembert-base-fquad | 87 | 3 | transformers | 4,855 | ---
language: fr
tags:
- question-answering
- camembert
license: gpl-3.0
datasets:
- fquad
---
# camembert-base-fquad
## Description
A native French Question Answering model [CamemBERT-base](https://camembert-model.fr/) fine-tuned on [FQuAD](https://fquad.illuin.tech/).
## Evaluation results
On the development set... |
mrm8488/layoutlm-finetuned-funsd | 3de04e17d2fb21729336dea31651b573e5e3c33a | 2021-08-01T16:39:26.000Z | [
"pytorch",
"layoutlm",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | mrm8488 | null | mrm8488/layoutlm-finetuned-funsd | 87 | null | transformers | 4,856 | # LayoutLM fine-tuned on FUNSD for Document/Forms token classification
## Usage (WIP)
```python
import torch
import numpy as np
from PIL import Image, ImageDraw, ImageFont
import pytesseract
from transformers import LayoutLMForTokenClassification, LayoutLMTokenizer
device = torch.device("cuda" if torch.cuda.is_avai... |
mrm8488/legalectra-small-spanish | 4854a72623057dcf56e51f7efb3a0cb15398388e | 2022-03-30T21:06:31.000Z | [
"pytorch",
"electra",
"pretraining",
"es",
"dataset:Spanish-legal-corpora",
"transformers",
"Spanish",
"Electra",
"Legal"
] | null | false | mrm8488 | null | mrm8488/legalectra-small-spanish | 87 | 2 | transformers | 4,857 | ---
language: es
tags:
- Spanish
- Electra
- Legal
datasets:
- Spanish-legal-corpora
---
## LEGALECTRA ⚖️
**LEGALECTRA** (small) is an Electra like model (discriminator in this case) trained on [A collection of corpora of Spanish legal domain](https://zenodo.org/record/5495529#.YZItp3vMLJw).
As mentioned in th... |
nateraw/test_model_a | 25e32086060f76efb5194dcb2db351b90ebf5981 | 2021-07-13T04:52:00.000Z | [
"pytorch",
"vit",
"image-classification",
"dataset:image_folder",
"transformers",
"generated_from_trainer"
] | image-classification | false | nateraw | null | nateraw/test_model_a | 87 | null | transformers | 4,858 | ---
tags:
- generated_from_trainer
datasets:
- image_folder
model_index:
- name: test_model_a
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
---
<!-- This model card has been generated automatical... |
mustapha/flipped-image-ViT | 3c76c3aa2325d0d5678c64e7b536ead6903e64b1 | 2022-03-31T12:30:19.000Z | [
"pytorch",
"vit",
"image-classification",
"transformers"
] | image-classification | false | mustapha | null | mustapha/flipped-image-ViT | 87 | 1 | transformers | 4,859 | Hello world,
This model have been created in the context of ` Fatima Fellowship Programme`. The model was trained on the Cifar10 dataset with a googd final accuracy of arround 98%.
This model determines wether an image is flipped of not. |
moshew/bert-mini-sst2-distilled | 61728bcf9f705e4161ee2be3185bfb48f7a1c617 | 2022-04-13T11:33:29.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers"
] | text-classification | false | moshew | null | moshew/bert-mini-sst2-distilled | 87 | null | transformers | 4,860 | Entry not found |
tinkoff-ai/response-quality-classifier-base | 4d3c0a32337d670038becdbd0478e85012795a3c | 2022-06-01T06:34:22.000Z | [
"pytorch",
"bert",
"text-classification",
"ru",
"transformers",
"conversational",
"license:mit"
] | text-classification | false | tinkoff-ai | null | tinkoff-ai/response-quality-classifier-base | 87 | null | transformers | 4,861 | ---
license: mit
widget:
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESPONSE_TOKEN]супер, вот только проснулся, у тебя как?"
example_title: "Dialog example 1"
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESPONSE_TOKEN]норм"
example_title: "Dialog example 2"
- text: "[CLS]привет[SEP]привет![SEP]как дела?[RESP... |
Theivaprakasham/layoutlmv3-finetuned-sroie | 6c8e3d5dcdf9e36ca53ad490f93714c44bbce3a3 | 2022-06-07T18:08:04.000Z | [
"pytorch",
"tensorboard",
"layoutlmv3",
"token-classification",
"dataset:sroie",
"transformers",
"generated_from_trainer",
"model-index",
"autotrain_compatible"
] | token-classification | false | Theivaprakasham | null | Theivaprakasham/layoutlmv3-finetuned-sroie | 87 | null | transformers | 4,862 | ---
tags:
- generated_from_trainer
datasets:
- sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-sroie
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: sroie
type: sroie
args: sroie
metrics:
- ... |
crumb/gpt-j-6b-shakespeare | eee121823da348a498f0f544c6afdb34c7880923 | 2022-07-20T18:06:37.000Z | [
"pytorch",
"gptj",
"text-generation",
"en",
"dataset:The Pile",
"dataset:tiny_shakespeare",
"arxiv:2101.00027",
"transformers",
"causal-lm"
] | text-generation | false | crumb | null | crumb/gpt-j-6b-shakespeare | 87 | null | transformers | 4,863 | ---
language:
- en
tags:
- pytorch
- causal-lm
datasets:
- The Pile
- tiny_shakespeare
inference: false
---
# GPT-J 6b Shakespeare
<p style="color:green"> <b> 1.) The "Hosted inference API" is turned off. Go to the <a href="https://huggingface.co/crumb/gpt-j-6b-shakespeare#how-to-use">How to Use</a> section <br>
2.) ... |
tilomichel/mT5-base-GermanQuAD-e2e-qg | 61f6573dde3826229f574d2aaf2ff4ea07d961cc | 2022-07-02T10:46:35.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"de",
"dataset:deepset/germanquad",
"arxiv:2010.11934",
"arxiv:2005.01107",
"transformers",
"question generation",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | tilomichel | null | tilomichel/mT5-base-GermanQuAD-e2e-qg | 87 | null | transformers | 4,864 | ---
license: mit
widget:
- text: "generate question: KMI ist eine Variante des allgemeinen Bachelors Informatik und damit zu ca. 80% identisch mit dem allgemeinen Bachelor Informatik, d.h. auch diese Variante ist ein Informatikstudium mit einem hohen Programmieranteil. Der Studienschwerpunkt adressiert insbesondere die... |
natalierobbins/test_model | 6229c433e4c8e29be7d43a783685b0345cf76bca | 2022-07-19T23:29:56.000Z | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | natalierobbins | null | natalierobbins/test_model | 87 | null | transformers | 4,865 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: test_model
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... |
abelblue3/DialoGPT-medium-baymax | 7e5216ccdbc9de4e8e2810f1bb38fadbcb8376de | 2022-07-29T17:08:22.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | false | abelblue3 | null | abelblue3/DialoGPT-medium-baymax | 87 | null | transformers | 4,866 | ---
tags:
- conversational
---
# DialoGPT BaymaxBot |
AkshatSurolia/DeiT-FaceMask-Finetuned | 7a7f81c61c64c9d0821d0a5d63d54fe9427ebde6 | 2022-02-18T13:10:05.000Z | [
"pytorch",
"deit",
"image-classification",
"dataset:Face-Mask18K",
"transformers",
"license:apache-2.0"
] | image-classification | false | AkshatSurolia | null | AkshatSurolia/DeiT-FaceMask-Finetuned | 86 | null | transformers | 4,867 | ---
license: apache-2.0
tags:
- image-classification
datasets:
- Face-Mask18K
---
# Distilled Data-efficient Image Transformer for Face Mask Detection
Distilled data-efficient Image Transformer (DeiT) model pre-trained and fine-tuned on Self Currated Custom Face-Mask18K Dataset (18k images, 2 classes) at r... |
BigSalmon/SimplifyText | f1dcd3f3a42cf9f8515c8177e341c506e24dd9d2 | 2021-10-14T00:41:11.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | BigSalmon | null | BigSalmon/SimplifyText | 86 | null | transformers | 4,868 | - All credit goes to https://huggingface.co/philippelaban/keep_it_simple.
- This is a copy of their repository for future training purposes.
- It is supposed to simplify text.
- Their model card gives instructions on how to use it. |
Geotrend/bert-base-en-th-cased | 336fd71f6da084fd96bc5cec3b745712333ba686 | 2021-05-18T19:47:11.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"multilingual",
"dataset:wikipedia",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | false | Geotrend | null | Geotrend/bert-base-en-th-cased | 86 | null | transformers | 4,869 | ---
language: multilingual
datasets: wikipedia
license: apache-2.0
widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
---
# bert-base-en-th-cased
We are sharing smaller versions of [bert-base-multilingual-cased... |
Helsinki-NLP/opus-mt-de-vi | ec56a3fd05ff4fba8acaa11a0d434e889b088cdd | 2021-01-18T08:02:50.000Z | [
"pytorch",
"marian",
"text2text-generation",
"de",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-de-vi | 86 | null | transformers | 4,870 | ---
language:
- de
- vi
tags:
- translation
license: apache-2.0
---
### deu-vie
* source group: German
* target group: Vietnamese
* OPUS readme: [deu-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-vie/README.md)
* model: transformer-align
* source language(s): deu
* target langu... |
Helsinki-NLP/opus-mt-gmw-gmw | 14861fa7cfac10a6f99c09e30a18c23cc02bf1b1 | 2021-01-18T08:53:04.000Z | [
"pytorch",
"marian",
"text2text-generation",
"nl",
"en",
"lb",
"af",
"de",
"fy",
"yi",
"gmw",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-gmw-gmw | 86 | null | transformers | 4,871 | ---
language:
- nl
- en
- lb
- af
- de
- fy
- yi
- gmw
tags:
- translation
license: apache-2.0
---
### gmw-gmw
* source group: West Germanic languages
* target group: West Germanic languages
* OPUS readme: [gmw-gmw](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/gmw-gmw/README.md)
* mode... |
Helsinki-NLP/opus-mt-ja-tr | ac9ece2f2c4dd604a6d69c927bef045f09295e5d | 2020-08-21T14:42:47.000Z | [
"pytorch",
"marian",
"text2text-generation",
"ja",
"tr",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-ja-tr | 86 | null | transformers | 4,872 | ---
language:
- ja
- tr
tags:
- translation
license: apache-2.0
---
### jpn-tur
* source group: Japanese
* target group: Turkish
* OPUS readme: [jpn-tur](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/jpn-tur/README.md)
* model: transformer-align
* source language(s): jpn jpn_Bopo jpn_Ha... |
NYTK/summarization-hi-bart-base-1024-hungarian | 89a30ed7fa730cd8068cf4931de9fd4b41b21334 | 2022-02-14T13:27:40.000Z | [
"pytorch",
"bart",
"text2text-generation",
"hu",
"transformers",
"summarization",
"license:gpl",
"autotrain_compatible"
] | summarization | false | NYTK | null | NYTK/summarization-hi-bart-base-1024-hungarian | 86 | null | transformers | 4,873 | ---
language:
- hu
tags:
- summarization
license: gpl
metrics:
- rouge
widget:
- text: "A Tisza-parti város állatkertjében régóta tartanak szurikátákat ( Suricata suricatta ) , de tavaly tavaszig nem sikerült szaporítani őket , annak ellenére , hogy tágas ház és kifutó épült számukra - közölte Veprik Róbert igazgat... |
benjamin/gpt2-wechsel-chinese | feee72e42c2b685b2db8905223633ae6ce92f20f | 2022-07-13T23:43:53.000Z | [
"pytorch",
"gpt2",
"text-generation",
"zh",
"transformers",
"license:mit"
] | text-generation | false | benjamin | null | benjamin/gpt2-wechsel-chinese | 86 | null | transformers | 4,874 | ---
language: zh
license: mit
---
# gpt2-wechsel-chinese
Model trained with WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
See the code here: https://github.com/CPJKU/wechsel
And the paper here: https://aclanthology.org/2022.naacl-main.293/
## Per... |
nates-test-org/convit_small | 0d0cc307c82f89aa6268ef668e056b1ba00c2fc1 | 2021-10-29T04:45:04.000Z | [
"pytorch",
"timm",
"image-classification"
] | image-classification | false | nates-test-org | null | nates-test-org/convit_small | 86 | null | timm | 4,875 | ---
tags:
- image-classification
- timm
library_tag: timm
---
# Model card for convit_small |
persiannlp/mt5-base-parsinlu-squad-reading-comprehension | 626121fa4a6a18daa743231abe29b3419c03cd61 | 2021-09-23T16:20:07.000Z | [
"pytorch",
"mt5",
"text2text-generation",
"fa",
"multilingual",
"dataset:parsinlu",
"dataset:squad",
"transformers",
"reading-comprehension",
"persian",
"farsi",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible"
] | text2text-generation | false | persiannlp | null | persiannlp/mt5-base-parsinlu-squad-reading-comprehension | 86 | 1 | transformers | 4,876 |
---
language:
- fa
- multilingual
thumbnail: https://upload.wikimedia.org/wikipedia/commons/a/a2/Farsi.svg
tags:
- reading-comprehension
- mt5
- persian
- farsi
license: cc-by-nc-sa-4.0
datasets:
- parsinlu
- squad
metrics:
- f1
---
# Reading Comprehension (مدل برای پاسخ به درک مطلب)
This is a mT5-based model for read... |
projecte-aina/roberta-base-ca-cased-ner | aa44b621c767260cafa37e060f4f8a251f619936 | 2022-06-15T07:55:56.000Z | [
"pytorch",
"roberta",
"token-classification",
"ca",
"dataset:projecte-aina/ancora-ca-ner",
"arxiv:1907.11692",
"transformers",
"catalan",
"named entity recognition",
"ner",
"CaText",
"Catalan Textual Corpus",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | projecte-aina | null | projecte-aina/roberta-base-ca-cased-ner | 86 | 1 | transformers | 4,877 | ---
language:
- ca
license: apache-2.0
tags:
- "catalan"
- "named entity recognition"
- "ner"
- "CaText"
- "Catalan Textual Corpus"
datasets:
- "projecte-aina/ancora-ca-ner"
metrics:
- f1
model-index:
- name: roberta-base-ca-cased-ner
results:
- task:
type: token-classification
dataset:
... |
remi/bertabs-finetuned-xsum-extractive-abstractive-summarization | a184879f346b3a77c35e9390c7e4a660cb2ef6e3 | 2021-05-20T04:17:40.000Z | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | remi | null | remi/bertabs-finetuned-xsum-extractive-abstractive-summarization | 86 | null | transformers | 4,878 | Entry not found |
nickmuchi/vit-finetuned-chest-xray-pneumonia | 2086fb41a4a93b6c7bf701ae8d068157591c8afb | 2022-03-09T12:50:04.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"dataset:chest X-rays",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | image-classification | false | nickmuchi | null | nickmuchi/vit-finetuned-chest-xray-pneumonia | 86 | null | transformers | 4,879 | ---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
datasets:
- chest X-rays
widget:
- src: https://drive.google.com/uc?id=1ygVCyEn6mfsNwpT1ZvWxANg5_DvStA7M
example_title: PNEUMONIA
- src: https://drive.google.com/uc?id=1xjcIEDb8kuSd4wF44gCEgsc0PfRvs53m
example_title: N... |
Alvenir/wav2vec2-base-da-ft-nst | f8e0c5370b6db09ff54eb8a15ed642f58eaae55f | 2022-03-17T16:16:12.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"da",
"transformers",
"speech-to-text",
"license:apache-2.0"
] | automatic-speech-recognition | false | Alvenir | null | Alvenir/wav2vec2-base-da-ft-nst | 86 | 3 | transformers | 4,880 | ---
language: da
tags:
- speech-to-text
license: apache-2.0
---
# wav2vec2-base-da-ft-nst
This the [alvenir wav2vec2 model](https://huggingface.co/Alvenir/wav2vec2-base-da) for Danish ASR finetuned by Alvenir on the public NST dataset. The model is trained on 16kHz, so make sure your data is the same sample r... |
ai4bharat/MultiIndicParaphraseGeneration | 3f5c5a06fa624a6267d93df3e8332197cc5cb6f5 | 2022-03-31T06:21:30.000Z | [
"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/MultiIndicParaphraseGeneration | 86 | null | transformers | 4,881 | ---
tags:
- paraphrase-generation
- multilingual
- nlp
- indicnlp
datasets:
- ai4bharat/IndicParaphrase
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
license:
- mit
---
# MultiIndicParaphraseGeneration
This repository contains the [IndicBART](https://huggingface.co/ai4... |
efederici/sentence-BERTino | 871f99951d3375f75a9cf7dc147cb1e0fac0170f | 2022-05-03T13:14:23.000Z | [
"pytorch",
"distilbert",
"feature-extraction",
"it",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | efederici | null | efederici/sentence-BERTino | 86 | 1 | sentence-transformers | 4,882 | ---
pipeline_tag: sentence-similarity
license: apache-2.0
language:
- it
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-BERTino
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector sp... |
NYTK/named-entity-recognition-nerkor-hubert-hungarian | a52a08bcc8abe9447ccc860f648b34500c130338 | 2022-04-01T09:03:27.000Z | [
"pytorch",
"bert",
"token-classification",
"hu",
"transformers",
"license:gpl",
"autotrain_compatible"
] | token-classification | false | NYTK | null | NYTK/named-entity-recognition-nerkor-hubert-hungarian | 86 | null | transformers | 4,883 | ---
language:
- hu
tags:
- token-classification
license: gpl
metrics:
- f1
widget:
- text: "A Kovácsné Nagy Erzsébet nagyon jól érzi magát a Nokiánál, azonban a Németországból érkezett Kovács Péter nehezen boldogul a beilleszkedéssel."
---
# Hungarian Sentence-level Sentiment Analysis model with XLM... |
IDEA-CCNL/Erlangshen-Roberta-330M-NLI | f42d4a45e9dc3933398be40431315edbd4e19c21 | 2022-05-12T09:49:11.000Z | [
"pytorch",
"bert",
"text-classification",
"zh",
"transformers",
"NLU",
"NLI",
"license:apache-2.0"
] | text-classification | false | IDEA-CCNL | null | IDEA-CCNL/Erlangshen-Roberta-330M-NLI | 86 | null | transformers | 4,884 | ---
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- NLI
inference: true
widget:
- text: "今天心情不好[SEP]今天很开心"
---
# Erlangshen-Roberta-330M-NLI, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
We collect 4 NLI（Natural Language Inference） datasets in the Chinese ... |
mary905el/ruT5_neuro_chgk_answering | 349381b078e48288d6b82e26d5cd5c68c5c369bb | 2022-04-27T05:33:03.000Z | [
"pytorch",
"t5",
"text2text-generation",
"ru",
"transformers",
"PyTorch",
"Transformers",
"autotrain_compatible"
] | text2text-generation | false | mary905el | null | mary905el/ruT5_neuro_chgk_answering | 86 | null | transformers | 4,885 | ---
language:
- ru
tags:
- PyTorch
- Transformers
widget:
- text: "Ответьте двумя словами, что мы заменили на ИКС?"
inference:
parameters:
do_sample: True
temperature: 0.8
---
This is https://huggingface.co/sberbank-ai/ruT5-base model, fine-tuned to answer ChGK questions (Что? Где? Когда? https://db.chgk.inf... |
smc/Electric_Pole_with_or_without_transformer | dc05ec14a729ac37195e2d0361cf279727d5f862 | 2022-05-21T22:09:33.000Z | [
"pytorch",
"tensorboard",
"vit",
"image-classification",
"transformers",
"huggingpics",
"model-index"
] | image-classification | false | smc | null | smc/Electric_Pole_with_or_without_transformer | 86 | 1 | transformers | 4,886 | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: Electric_Pole_with_or_without_transformer
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9230769276618958... |
qalover/chinese-pert-large-open-domain-mrc | e9cfdc887fe9d6cb043fb9b870e1908067e31916 | 2022-05-31T14:21:54.000Z | [
"pytorch",
"bert",
"question-answering",
"zh",
"transformers",
"license:gpl-3.0",
"autotrain_compatible"
] | question-answering | false | qalover | null | qalover/chinese-pert-large-open-domain-mrc | 86 | 1 | transformers | 4,887 | ---
language:
- zh
license: gpl-3.0
---
## 基于 chinese-pert-large 训练的面向开放领域MRC 模型
使用中文MRC数据（cmrc2018, webqa与laisi的训练集）训练的chinese-pert-large模型
## 训练过程
使用了[UER-py](https://github.com/dbiir/UER-py/) 进行fine-tuned
加入了包括但不限于摘要、负采样、混淆等数据加强方法
并转换为Huggingface进行上传
| | CMRC 2018 Dev | DRCD Dev | SQuAD-Zen Dev (A... |
renjithks/layoutlmv2-er-ner | 2edce8c45d8a8307630be7e53eff3d362a74bb6e | 2022-06-08T19:37:51.000Z | [
"pytorch",
"tensorboard",
"layoutlmv2",
"token-classification",
"transformers",
"generated_from_trainer",
"license:cc-by-nc-sa-4.0",
"model-index",
"autotrain_compatible"
] | token-classification | false | renjithks | null | renjithks/layoutlmv2-er-ner | 86 | null | transformers | 4,888 | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv2-er-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... |
fusing/latent-diffusion-text2im-large | 030d95399e64c1ff7be798e62b9bc6ef6ec7bf3b | 2022-07-18T13:31:27.000Z | [
"pytorch",
"ldmbert",
"arxiv:2112.10752",
"transformers",
"diffusion",
"license:mit"
] | null | false | fusing | null | fusing/latent-diffusion-text2im-large | 86 | 2 | transformers | 4,889 | ---
tags:
- diffusion
license: mit
---
Latent Diffusion
**Paper**: [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/abs/2112.10752)
**Abstract**:
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state... |
tornqvistmax/7cats_finetuned | f747e28016a4aacf52435f263855c669bcd421d1 | 2022-06-16T14:43:45.000Z | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | false | tornqvistmax | null | tornqvistmax/7cats_finetuned | 86 | null | transformers | 4,890 | Entry not found |
Vlasta/DNADebertaK7 | ba8d72bc65ce662e14e0ecf36a815ed003beb5f5 | 2022-07-05T23:37:40.000Z | [
"pytorch",
"deberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | Vlasta | null | Vlasta/DNADebertaK7 | 86 | null | transformers | 4,891 | Entry not found |
Chrode/bert_prot_temp_classifier | e86766a768e54af94880b3955b93b6bc08bd624c | 2022-07-04T07:54:58.000Z | [
"pytorch",
"BertTempProtClassifier",
"transformers"
] | null | false | Chrode | null | Chrode/bert_prot_temp_classifier | 86 | null | transformers | 4,892 | Entry not found |
darragh/swinunetr-btcv-tiny | ce084bb73ca3af65aa33b79a8d00eab93550122e | 2022-07-15T21:01:18.000Z | [
"pytorch",
"en",
"dataset:BTCV",
"transformers",
"btcv",
"medical",
"swin",
"license:apache-2.0"
] | null | false | darragh | null | darragh/swinunetr-btcv-tiny | 86 | null | transformers | 4,893 | ---
language: en
tags:
- btcv
- medical
- swin
license: apache-2.0
datasets:
- BTCV
---
# Model Overview
This repository contains the code for Swin UNETR [1,2]. Swin UNETR is the state-of-the-art on Medical Segmentation
Decathlon (MSD) and Beyond the Cranial Vault (BTCV) Segmentation Challenge dataset. In [1], a nove... |
Helsinki-NLP/opus-mt-fr-vi | d7a313fa61fa59ee759fd877759de83fd244dce8 | 2021-01-18T08:49:25.000Z | [
"pytorch",
"marian",
"text2text-generation",
"fr",
"vi",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | false | Helsinki-NLP | null | Helsinki-NLP/opus-mt-fr-vi | 85 | null | transformers | 4,894 | ---
language:
- fr
- vi
tags:
- translation
license: apache-2.0
---
### fra-vie
* source group: French
* target group: Vietnamese
* OPUS readme: [fra-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-vie/README.md)
* model: transformer-align
* source language(s): fra
* target langu... |
KrishParikh/gpt2_imdb_movie_plots | ab4a551b10ca184133e3c2a3e213b71d3495f65c | 2021-11-21T20:11:06.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"model-index"
] | text-generation | false | KrishParikh | null | KrishParikh/gpt2_imdb_movie_plots | 85 | null | transformers | 4,895 | ---
tags:
- generated_from_trainer
model-index:
- name: gpt2-plot
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. -->
# gpt2-plot
This model is a fine-tuned version... |
SkolkovoInstitute/roberta_toxicity_classifier_v1 | 0aeddbf4acc227b80ca3a5e2409c26b0988639a2 | 2021-11-02T18:36:13.000Z | [
"pytorch",
"roberta",
"text-classification",
"arxiv:1911.00536",
"transformers"
] | text-classification | false | SkolkovoInstitute | null | SkolkovoInstitute/roberta_toxicity_classifier_v1 | 85 | null | transformers | 4,896 | This model is a clone of [SkolkovoInstitute/roberta_toxicity_classifier](https://huggingface.co/SkolkovoInstitute/roberta_toxicity_classifier) trained on a disjoint dataset.
While `roberta_toxicity_classifier` is used for evaluation of detoxification algorithms, `roberta_toxicity_classifier_v1` can be used within the... |
TODBERT/TOD-DistilBERT-JNT-V1 | c21cde3992721781e96604a7030de7bff81dc663 | 2020-08-26T18:39:56.000Z | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | TODBERT | null | TODBERT/TOD-DistilBERT-JNT-V1 | 85 | null | transformers | 4,897 | Entry not found |
YituTech/conv-bert-medium-small | 4889125682c36c29e56dd0a70717c8706ef1333a | 2021-02-24T11:24:27.000Z | [
"pytorch",
"tf",
"convbert",
"feature-extraction",
"transformers"
] | feature-extraction | false | YituTech | null | YituTech/conv-bert-medium-small | 85 | null | transformers | 4,898 | Entry not found |
dbernsohn/roberta-python | cb9ceb18059e5edec8431480d2a21f749b5b4fca | 2021-05-20T15:57:13.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"python",
"dataset:code_search_net",
"arxiv:1907.11692",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbernsohn | null | dbernsohn/roberta-python | 85 | 3 | transformers | 4,899 | # roberta-python
---
language: python
datasets:
- code_search_net
---
This is a [roberta](https://arxiv.org/pdf/1907.11692.pdf) pre-trained version on the [CodeSearchNet dataset](https://github.com/github/CodeSearchNet) for **Python** Mask Language Model mission.
To load the model:
(necessary packages: !pip install t... |
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