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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bhavikardeshna/xlm-roberta-base-german | 530e8c3dd543800078c3dfbfcde30c883480f258 | 2021-12-21T11:40:35.000Z | [
"pytorch",
"xlm-roberta",
"question-answering",
"arxiv:2112.09866",
"transformers",
"autotrain_compatible"
] | question-answering | false | bhavikardeshna | null | bhavikardeshna/xlm-roberta-base-german | 15 | null | transformers | 9,500 | # BibTeX entry and citation info
```
@misc{pandya2021cascading,
title={Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages},
author={Hariom A. Pandya and Bhavik Ardeshna and Dr. Brijesh S. Bhatt},
year={2021},
eprint={2112.09866},... |
bs-modeling-metadata/website_metadata_exp_1_model_100k_checkpoint | 875249e5fc9357a93f6eab4461688b3ac18d40dc | 2021-10-07T13:32:07.000Z | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | bs-modeling-metadata | null | bs-modeling-metadata/website_metadata_exp_1_model_100k_checkpoint | 15 | 1 | transformers | 9,501 | Entry not found |
bsingh/roberta_goEmotion | af498dcbab4ef49f7163cac455aa0d34ae7d25d8 | 2021-10-11T00:26:09.000Z | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:go_emotions",
"transformers",
"emotions",
"license:mit"
] | text-classification | false | bsingh | null | bsingh/roberta_goEmotion | 15 | null | transformers | 9,502 | ---
language: en
tags:
- text-classification
- pytorch
- roberta
- emotions
datasets:
- go_emotions
license: mit
widget:
- text: "I am not feeling well today."
---
## This model is trained for GoEmotions dataset which contains labeled 58k Reddit comments with 28 emotions
- admiration, amusement, anger, annoyance, appr... |
cardiffnlp/bertweet-base-stance-atheism | 8a4275b426ee8d4136b36ed826bd3feb2dc41f3c | 2021-05-20T14:53:17.000Z | [
"pytorch",
"tf",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | cardiffnlp | null | cardiffnlp/bertweet-base-stance-atheism | 15 | null | transformers | 9,503 | |
chrommium/rubert-base-cased-sentence-finetuned-headlines_X | 3ff3429c5539d43e2a02328421cf8204c67695e4 | 2021-09-16T00:34:06.000Z | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"transformers",
"generated_from_trainer",
"model-index"
] | text-classification | false | chrommium | null | chrommium/rubert-base-cased-sentence-finetuned-headlines_X | 15 | null | transformers | 9,504 | ---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: rubert-base-cased-sentence-finetuned-headlines_X
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.952
---
<!-- This model card has been g... |
classla/bcms-bertic-frenk-hate | f41364e4a917e75feddf03e7525b9aa001650aca | 2022-06-01T09:31:46.000Z | [
"pytorch",
"bert",
"text-classification",
"hr",
"arxiv:1906.02045",
"transformers",
"hate-speech"
] | text-classification | false | classla | null | classla/bcms-bertic-frenk-hate | 15 | null | transformers | 9,505 | ---
language: "hr"
tags:
- text-classification
- hate-speech
widget:
- text: "Potpredsjednik Vlade i ministar branitelja Tomo Medved komentirao je Vladine planove za zakonsku zabranu pozdrava 'za dom spremni'."
---
# bcms-bertic-frenk-hate
Text classification model based on [`classla/bcms-bertic`](https://huggingfac... |
crystina-z/monoELECTRA_LCE_nneg31 | 47923dbe2fb0dedea1c1572940b1289806838a92 | 2022-02-11T18:02:52.000Z | [
"pytorch",
"tf",
"electra",
"text-classification",
"transformers"
] | text-classification | false | crystina-z | null | crystina-z/monoELECTRA_LCE_nneg31 | 15 | null | transformers | 9,506 | Entry not found |
dbmdz/electra-base-german-europeana-cased-generator | 195c6427c576e68a7c2a97de2e20421fc506c58c | 2020-07-26T00:53:55.000Z | [
"pytorch",
"tf",
"electra",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | dbmdz | null | dbmdz/electra-base-german-europeana-cased-generator | 15 | null | transformers | 9,507 | Entry not found |
fabriceyhc/bert-base-uncased-yahoo_answers_topics | 968176fc24a2eb73cac26ab4312d8b22da98486a | 2021-09-21T00:54:22.000Z | [
"pytorch",
"bert",
"text-classification",
"dataset:yahoo_answers_topics",
"transformers",
"generated_from_trainer",
"sibyl",
"license:apache-2.0",
"model-index"
] | text-classification | false | fabriceyhc | null | fabriceyhc/bert-base-uncased-yahoo_answers_topics | 15 | 1 | transformers | 9,508 | ---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- yahoo_answers_topics
metrics:
- accuracy
model-index:
- name: bert-base-uncased-yahoo_answers_topics
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yahoo_answers_topics
type: y... |
fbaigt/procbert | 20814e122765866e213447ebe2618d2f0b90cbf1 | 2021-11-08T15:08:01.000Z | [
"pytorch",
"bert",
"feature-extraction",
"en",
"dataset:pubmed",
"dataset:chemical patent",
"dataset:cooking recipe",
"arxiv:2109.04711",
"transformers"
] | feature-extraction | false | fbaigt | null | fbaigt/procbert | 15 | 1 | transformers | 9,509 | ---
language:
- en
datasets:
- pubmed
- chemical patent
- cooking recipe
---
## ProcBERT
ProcBERT is a pre-trained language model specifically for procedural text. It was pre-trained on a large-scale procedural corpus (PubMed articles/chemical patents/cooking recipes) containing over 12B tokens and shows great perform... |
federicopascual/finetune-sentiment-analysis-model-3000-samples | 595ae6575f96bc971fd033b3560a98e80ede9517 | 2021-12-30T19:29:48.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | federicopascual | null | federicopascual/finetune-sentiment-analysis-model-3000-samples | 15 | null | transformers | 9,510 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetune-sentiment-analysis-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: plain_text
... |
figurative-nlp/t5-figurative-paraphrase | 4c382b695540ace5fa8ce647e3fcd67a372a93f8 | 2022-02-17T12:21:53.000Z | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | figurative-nlp | null | figurative-nlp/t5-figurative-paraphrase | 15 | 2 | transformers | 9,511 | This model can convert the figurative/metaphorical expression to the literal expression. Below is the usage of our model:
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("figurative-nlp/t5-figurative-paraphrase")
model = AutoModelForSeq2SeqLM.fr... |
fnlp/elasticbert-large | 0a5689cea93ed0bf88c87bcd623e0de0f98516e2 | 2021-10-28T11:05:49.000Z | [
"pytorch",
"elasticbert",
"fill-mask",
"arxiv:2110.07038",
"transformers",
"autotrain_compatible"
] | fill-mask | false | fnlp | null | fnlp/elasticbert-large | 15 | 2 | transformers | 9,512 | # ElasticBERT-LARGE
## Model description
This is an implementation of the `large` version of ElasticBERT.
[**Towards Efficient NLP: A Standard Evaluation and A Strong Baseline**](https://arxiv.org/pdf/2110.07038.pdf)
Xiangyang Liu, Tianxiang Sun, Junliang He, Lingling Wu, Xinyu Zhang, Hao Jiang, Zhao Cao, Xuanjing ... |
geekfeed/gpt2_ja | 6c297f7e58fc6e7c75d654941380620cd3710660 | 2021-05-21T16:11:52.000Z | [
"pytorch",
"jax",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | false | geekfeed | null | geekfeed/gpt2_ja | 15 | null | transformers | 9,513 | hello
|
ghadeermobasher/BC2GM-Gene-Modified_scibert_scivocab_cased | cf11c70aceb0994ec32ebedfa0a2e878043b12f9 | 2022-01-23T19:55:04.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC2GM-Gene-Modified_scibert_scivocab_cased | 15 | null | transformers | 9,514 | Entry not found |
ghadeermobasher/BC2GM-Gene_ImbalancedPubMedBERT | 2574cb8b0ee0fe4af0e9b272c51f855bfa3c1b01 | 2022-01-22T01:44:25.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC2GM-Gene_ImbalancedPubMedBERT | 15 | null | transformers | 9,515 | Entry not found |
ghadeermobasher/BC4-Original-biobert-v1.1 | ab10a139dbc7b0c0c9bc6a4558a206e5d73fb3e5 | 2022-02-24T14:45:29.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4-Original-biobert-v1.1 | 15 | null | transformers | 9,516 | Entry not found |
ghadeermobasher/BC4-Original-bluebert_pubmed_uncased_L-12_H-768_A-12 | cbceb41840ab0b1b4d9cd8d4cc7a19ac477fae8d | 2022-02-24T14:22:37.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4-Original-bluebert_pubmed_uncased_L-12_H-768_A-12 | 15 | null | transformers | 9,517 | Entry not found |
ghadeermobasher/BC4-Original-scibert_scivocab_uncased | 1bb6e36961e4a831a996c806637ac891282bf3e9 | 2022-02-24T14:28:32.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4-Original-scibert_scivocab_uncased | 15 | null | transformers | 9,518 | Entry not found |
ghadeermobasher/BC5CDR-Chemical-imbalanced-bluebert_pubmed_uncased_L-12_H-768_A-12_latest | 17f9443fd2d369763bf7c64b4eb9206803f0df27 | 2022-02-21T23:07:06.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC5CDR-Chemical-imbalanced-bluebert_pubmed_uncased_L-12_H-768_A-12_latest | 15 | null | transformers | 9,519 | Entry not found |
glasses/resnet18 | a15b2ef76c4e01cc6b3f4518f56c1c98722d6793 | 2021-11-30T20:06:28.000Z | [
"pytorch",
"dataset:imagenet",
"arxiv:1512.03385",
"arxiv:1812.01187",
"transformers",
"image-classification",
"license:apache-2.0"
] | image-classification | false | glasses | null | glasses/resnet18 | 15 | null | transformers | 9,520 | ---
license: apache-2.0
tags:
- image-classification
datasets:
- imagenet
---
# resnet18
Implementation of ResNet proposed in [Deep Residual Learning for Image
Recognition](https://arxiv.org/abs/1512.03385)
``` python
ResNet.resnet18()
ResNet.resnet26()
ResNet.resnet34()
ResNet.resnet50()
ResNet.resnet101()
Res... |
gpssohi/distilbart-qgen-3-3 | 66e9d4f41a1c4bf55bdab0a9eb904476542d5d06 | 2022-01-12T08:29:26.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:squad",
"transformers",
"question-generation",
"summarization",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | gpssohi | null | gpssohi/distilbart-qgen-3-3 | 15 | 2 | transformers | 9,521 | ---
language: en
tags:
- question-generation
- summarization
license: apache-2.0
datasets:
- squad
---
# Introduction
This model checkpoint is obtained by first fine-tuning the sshleifer/distilbart-cnn-6-6 summarization checkpoint on the SQuAD dataset. After this, the 6-6 fine-tuned model is distilled down to a 3-3 m... |
gpssohi/distilbart-qgen-6-6 | 18d85ee5d5482d7af7b5f719048f4bc641c3a5ff | 2022-01-12T08:29:13.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"dataset:squad",
"transformers",
"summarization",
"question-generation",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | false | gpssohi | null | gpssohi/distilbart-qgen-6-6 | 15 | 1 | transformers | 9,522 | ---
language: en
tags:
- summarization
- question-generation
license: apache-2.0
datasets:
- squad
---
# Introduction
This model checkpoint is obtained by fine-tuning the `sshleifer/distilbart-cnn-6-6` summarization checkpoint on the SQuAD dataset. [GitHub Link for training scripts.](https://github.com/darth-c0d3r/ba... |
gwkim22/domain_base2_disc | 253c926654ffcae55fe363bca751474d03b90ec7 | 2021-07-19T01:56:14.000Z | [
"pytorch",
"electra",
"pretraining",
"transformers"
] | null | false | gwkim22 | null | gwkim22/domain_base2_disc | 15 | 1 | transformers | 9,523 | "domain_base2_disc_0719"
|
hamzaMM/questionClassifier | d1d326c6965fb4f91070df4356562dade3b37364 | 2021-12-02T20:08:26.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | hamzaMM | null | hamzaMM/questionClassifier | 15 | 2 | transformers | 9,524 | Entry not found |
hrdipto/wav2vec2-xls-r-300m-bangla-command-generated-data-finetune | 6361d8dfe95c21a0fe20389a195e9de9aab1de02 | 2022-02-14T08:58:20.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"model-index"
] | automatic-speech-recognition | false | hrdipto | null | hrdipto/wav2vec2-xls-r-300m-bangla-command-generated-data-finetune | 15 | null | transformers | 9,525 | ---
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-xls-r-300m-bangla-command-generated-data-finetune
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. -->... |
huggingartists/kanye-west | ef0b90df2f597af17783d7ae3477a01de520f35c | 2022-05-05T00:27:21.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"dataset:huggingartists/kanye-west",
"transformers",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm"
] | text-generation | false | huggingartists | null | huggingartists/kanye-west | 15 | null | transformers | 9,526 | ---
language: en
datasets:
- huggingartists/kanye-west
tags:
- huggingartists
- lyrics
- lm-head
- causal-lm
widget:
- text: "I am"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; heigh... |
huggingtweets/amazon | 7bc08510372ae3b213814f77f110ae1f3138dd3a | 2021-05-21T18:33:06.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/amazon | 15 | null | transformers | 9,527 | ---
language: en
thumbnail: https://www.huggingtweets.com/amazon/1609713999453/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
<style>
@media (prefers-color-scheme: dark) {
.prose { color: ... |
huggingtweets/deepleffen | 9f6a7a1f1bb73ef33f7cead6ee0b72ba37411d4f | 2022-06-03T17:34:54.000Z | [
"pytorch",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/deepleffen | 15 | null | transformers | 9,528 | ---
language: en
thumbnail: http://www.huggingtweets.com/deepleffen/1654277690184/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; widt... |
huggingtweets/nvidia | cceee848844258789df63f96b72b676fade2a4aa | 2021-05-22T17:00:36.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"en",
"transformers",
"huggingtweets"
] | text-generation | false | huggingtweets | null | huggingtweets/nvidia | 15 | null | transformers | 9,529 | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
<style>
@media (prefers-color-scheme: dark) {
.pros... |
imzachjohnson/autonlp-spinner-check-16492731 | 3e96dbddaf4b1b2c760fbf196391ac77ecfc7890 | 2021-10-11T00:02:11.000Z | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:imzachjohnson/autonlp-data-spinner-check",
"transformers",
"autonlp"
] | text-classification | false | imzachjohnson | null | imzachjohnson/autonlp-spinner-check-16492731 | 15 | null | transformers | 9,530 | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- imzachjohnson/autonlp-data-spinner-check
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 16492731
## Validation Metrics
- Loss: 0.21610039472579956
- Accuracy: 0.9155366722657816
- Precision: 0.9530714... |
jaimin/plagiarism_checker | 63fdab21cd1ee8fa220533eeb00c77238156728f | 2021-08-20T05:44:24.000Z | [
"pytorch",
"longformer",
"text-classification",
"transformers"
] | text-classification | false | jaimin | null | jaimin/plagiarism_checker | 15 | null | transformers | 9,531 | "hello"
|
kanishka/GlossBERT | 0cc3b83af5496e27ebcc95ef0cf37ea0a9281a7a | 2021-09-22T08:54:41.000Z | [
"pytorch",
"bert",
"en",
"dataset:SemCor3.0",
"arxiv:1908.07245",
"transformers",
"glossbert",
"license:mit"
] | null | false | kanishka | null | kanishka/GlossBERT | 15 | null | transformers | 9,532 | ---
language: en
tags:
- glossbert
license: mit
datasets:
- SemCor3.0
---
## GlossBERT
A BERT-based model fine-tuned on SemCor 3.0 to perform word-sense-disambiguation by leveraging gloss information. This model is the research output of the paper titled: '[GlossBERT: BERT for Word Sense Disambiguation with Gloss Kno... |
keshan/sinhala-roberta-oscar | 655873a1b237c7e09c424d0a55bb9fb05456248e | 2021-07-14T06:28:47.000Z | [
"pytorch",
"jax",
"tensorboard",
"roberta",
"fill-mask",
"si",
"dataset:oscar",
"arxiv:1907.11692",
"transformers",
"oscar",
"Sinhala",
"autotrain_compatible"
] | fill-mask | false | keshan | null | keshan/sinhala-roberta-oscar | 15 | null | transformers | 9,533 | ---
language: si
tags:
- oscar
- Sinhala
- roberta
- fill-mask
widget:
- text: "මම සිංහල භාෂාව <mask>"
datasets:
- oscar
---
### Overview
This is a slightly smaller model trained on [OSCAR](https://oscar-corpus.com/) Sinhala dedup dataset. As Sinhala is one of those low resource languages, there are only a handful of ... |
kurianbenoy/distilbert-base-uncased-finetuned-sst-2-english-finetuned-imdb | 465c2a001ccd95ff2faee805ffe909ef79fdf366 | 2022-02-21T11:55:41.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:imdb",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | kurianbenoy | null | kurianbenoy/distilbert-base-uncased-finetuned-sst-2-english-finetuned-imdb | 15 | null | transformers | 9,534 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sst-2-english-finetuned-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
args: ... |
leonardvorbeck/wav2vec2-large-robust-SB300 | e630e8662f2d52c6be25ccd3e95ba417f7c8b21b | 2021-08-26T12:22:18.000Z | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"en",
"dataset:libri_light",
"dataset:common_voice",
"dataset:switchboard",
"dataset:fisher",
"arxiv:2104.01027",
"transformers",
"speech",
"CTC",
"Attention",
"license:apache-2.0"
] | automatic-speech-recognition | false | leonardvorbeck | null | leonardvorbeck/wav2vec2-large-robust-SB300 | 15 | 1 | transformers | 9,535 | ---
language: en
datasets:
- libri_light
- common_voice
- switchboard
- fisher
tags:
- speech
- automatic-speech-recognition
- CTC
- Attention
- wav2vec2
license: apache-2.0
---
# Wav2Vec2-Large-Robust - Finetuned on Switchboard (300 hours)
## Note : Model has not been initialized. If you want to use it without furth... |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5 | 45fa2fa42a97b0478a98380d53a7a50ad0177cec | 2021-10-26T11:37:15.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5 | 15 | null | transformers | 9,536 | Entry not found |
luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_norm_bb_mlm_loss | ef1df072f813dcd203c30e97b7b273ed1f4e33ad | 2021-10-26T04:03:29.000Z | [
"pytorch",
"roberta",
"transformers"
] | null | false | luffycodes | null | luffycodes/bb_narataka_roberta_large_nli_bsz_16_bb_bsz_16_nli_lr_1e5_bb_lr_1e5_norm_bb_mlm_loss | 15 | null | transformers | 9,537 | Entry not found |
m3hrdadfi/zabanshenas-roberta-base-mix | a82c58d3632aaedec457182ea6e65d523fc960b0 | 2021-06-24T19:40:27.000Z | [
"pytorch",
"tf",
"roberta",
"text-classification",
"multilingual",
"dataset:wili_2018",
"transformers",
"license:apache-2.0"
] | text-classification | false | m3hrdadfi | null | m3hrdadfi/zabanshenas-roberta-base-mix | 15 | 1 | transformers | 9,538 | ---
language: multilingual
license: apache-2.0
datasets:
- wili_2018
---
# Zabanshenas - Language Detector
Zabanshenas is a Transformer-based solution for identifying the most likely language of a written document/text. Zabanshenas is a Persian word that has two meanings:
- A person who studies linguistics.
- A way ... |
manishiitg/output | 5ddc5ec9f5bf098c3e9de99c27773112ce34c510 | 2021-05-20T17:44:39.000Z | [
"pytorch",
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | manishiitg | null | manishiitg/output | 15 | null | transformers | 9,539 | Entry not found |
mbeukman/xlm-roberta-base-finetuned-kinyarwanda-finetuned-ner-swahili | ab8ad3c070d1fea9b697c2870129bca2d4a6f760 | 2021-11-25T09:04:07.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"sw",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-kinyarwanda-finetuned-ner-swahili | 15 | null | transformers | 9,540 | ---
language:
- sw
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Wizara ya afya ya Tanzania imeripoti Jumatatu kuwa , watu takriban 14 zaidi wamepata maambukizi ya Covid - 19 ."
---
# xlm-roberta-base-finetuned-kinyarwanda-finetuned-ner-swahili
This is a token classificatio... |
mbeukman/xlm-roberta-base-finetuned-ner-swahili | d09c7418ffdc293886fb957cc014eadacd60718b | 2021-11-25T09:04:40.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"sw",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-ner-swahili | 15 | 1 | transformers | 9,541 | ---
language:
- sw
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Wizara ya afya ya Tanzania imeripoti Jumatatu kuwa , watu takriban 14 zaidi wamepata maambukizi ya Covid - 19 ."
---
# xlm-roberta-base-finetuned-ner-swahili
This is a token classification (specifically NER) m... |
mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-luo | 728511ffd5d6856f5d75db779b2719d53ab75f07 | 2021-11-25T09:04:58.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"luo",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-swahili-finetuned-ner-luo | 15 | null | transformers | 9,542 | ---
language:
- luo
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Jii 2 moko jowito ngimagi ka machielo 1 to ohinyore marach mokalo e masira makoch mar apaya mane otimore e apaya mawuok Oyugis kochimo Chabera e sub county ma Rachuonyo East e County ma Homa Bay ewii odhiambo ... |
mbeukman/xlm-roberta-base-finetuned-yoruba-finetuned-ner-swahili | 80a0b4230b7b706e50ce5038e9f18b21f44c1198 | 2021-11-25T09:05:15.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"sw",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"NER",
"autotrain_compatible"
] | token-classification | false | mbeukman | null | mbeukman/xlm-roberta-base-finetuned-yoruba-finetuned-ner-swahili | 15 | null | transformers | 9,543 | ---
language:
- sw
tags:
- NER
datasets:
- masakhaner
metrics:
- f1
- precision
- recall
widget:
- text: "Wizara ya afya ya Tanzania imeripoti Jumatatu kuwa , watu takriban 14 zaidi wamepata maambukizi ya Covid - 19 ."
---
# xlm-roberta-base-finetuned-yoruba-finetuned-ner-swahili
This is a token classification (sp... |
meghanabhange/hinglish-sentence-bert | f7e2387d18a11062ab0ba7eb2919ee70d41d3795 | 2021-05-19T23:17:18.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | meghanabhange | null | meghanabhange/hinglish-sentence-bert | 15 | null | transformers | 9,544 | Entry not found |
midas/gupshup_e2e_pegasus | 4ddf0da7354c31ae27cdce2436ba6b87c6d21537 | 2021-11-14T02:07:37.000Z | [
"pytorch",
"pegasus",
"text2text-generation",
"arxiv:1910.04073",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | midas | null | midas/gupshup_e2e_pegasus | 15 | null | transformers | 9,545 | # Gupshup
GupShup: Summarizing Open-Domain Code-Switched Conversations EMNLP 2021
Paper: [https://aclanthology.org/2021.emnlp-main.499.pdf](https://aclanthology.org/2021.emnlp-main.499.pdf)
Github: [https://github.com/midas-research/gupshup](https://github.com/midas-research/gupshup)
### Dataset
Please request for the... |
mmcquade11/reviews-sentiment-analysis | 312c90a7ffe06f57619b45485e136e2c22c973b1 | 2021-12-01T18:52:49.000Z | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | mmcquade11 | null | mmcquade11/reviews-sentiment-analysis | 15 | null | transformers | 9,546 | Entry not found |
mofawzy/bert-ajgt | 2b31eb1e999581c5ccc7cf3c7d47ca3d2f9f50a0 | 2022-02-17T19:56:26.000Z | [
"pytorch",
"bert",
"text-classification",
"ar",
"dataset:AJGT",
"transformers",
"AJGT"
] | text-classification | false | mofawzy | null | mofawzy/bert-ajgt | 15 | null | transformers | 9,547 | ---
language:
- ar
datasets:
- AJGT
tags:
- AJGT
widget:
- text: "يهدي الله من يشاء"
- text: "الاسلوب قذر وقمامه"
---
# BERT-AJGT
Arabic version bert model fine tuned on AJGT dataset
## Data
The model were fine-tuned on ~1800 sentence from twitter for Jordanian dialect.
## Results
| class | precision | rec... |
monologg/koelectra-small-generator | a7d050043fdb98b63ebcb747df7004b5b94dc3b8 | 2020-12-26T16:23:42.000Z | [
"pytorch",
"electra",
"fill-mask",
"ko",
"transformers",
"autotrain_compatible"
] | fill-mask | false | monologg | null | monologg/koelectra-small-generator | 15 | null | transformers | 9,548 | ---
language: ko
---
# KoELECTRA (Small Generator)
Pretrained ELECTRA Language Model for Korean (`koelectra-small-generator`)
For more detail, please see [original repository](https://github.com/monologg/KoELECTRA/blob/master/README_EN.md).
## Usage
### Load model and tokenizer
```python
>>> from transformers imp... |
monsoon-nlp/es-seq2seq-gender-decoder | e271163d2c94e74e2ebba5315c4c0d1e7e598ac2 | 2021-05-20T00:09:13.000Z | [
"pytorch",
"bert",
"text-generation",
"es",
"transformers"
] | text-generation | false | monsoon-nlp | null | monsoon-nlp/es-seq2seq-gender-decoder | 15 | null | transformers | 9,549 | ---
language: es
---
# es-seq2seq-gender (decoder)
This is a seq2seq model (decoder half) to "flip" gender in Spanish sentences.
The model can augment your existing Spanish data, or generate counterfactuals
to test a model's decisions (would changing the gender of the subject or speaker change output?).
Intended Exa... |
monsoon-nlp/gpt-nyc | b49baf5fe2c2c03d309cbf681fd630ff15c564b9 | 2021-05-23T10:03:21.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | monsoon-nlp | null | monsoon-nlp/gpt-nyc | 15 | 1 | transformers | 9,550 | # GPT-NYC
## About
GPT2-Medium fine-tuned on questions and responses from https://reddit.com/r/asknyc
I filtered comments to ones with scores >= 3, and responding directly
to the original post ( = ignoring responses to other commenters).
I added tokens to match NYC neighborhoods, subway stations, foods, and other
c... |
mrm8488/GPT-2-finetuned-CRD3 | ce6e1457142a7aa61c564e5e32364f40f8cd3201 | 2021-05-23T10:10:58.000Z | [
"pytorch",
"jax",
"gpt2",
"text-generation",
"transformers"
] | text-generation | false | mrm8488 | null | mrm8488/GPT-2-finetuned-CRD3 | 15 | null | transformers | 9,551 | Entry not found |
mrm8488/spanbert-base-finetuned-squadv1 | 54aff17ce703bd24116984d9abbd019c06253159 | 2021-05-20T00:49:33.000Z | [
"pytorch",
"jax",
"bert",
"en",
"arxiv:1907.10529",
"transformers"
] | null | false | mrm8488 | null | mrm8488/spanbert-base-finetuned-squadv1 | 15 | null | transformers | 9,552 | ---
language: en
thumbnail:
---
# SpanBERT base fine-tuned on SQuAD v1
[SpanBERT](https://github.com/facebookresearch/SpanBERT) created by [Facebook Research](https://github.com/facebookresearch) and fine-tuned on [SQuAD 1.1](https://rajpurkar.github.io/SQuAD-explorer/explore/1.1/dev/) for **Q&A** downstream task ([b... |
ncoop57/cm_codeparrot | e21e05b4fa4c25b96a6f18f8ff8097628257550d | 2022-03-02T12:59:23.000Z | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | false | ncoop57 | null | ncoop57/cm_codeparrot | 15 | null | transformers | 9,553 | Entry not found |
nielsr/dino_deits8 | 161957bc7e0712f3c5bd5490e62ae9c70678ae4c | 2021-05-03T08:17:02.000Z | [
"pytorch",
"vit",
"feature-extraction",
"transformers"
] | feature-extraction | false | nielsr | null | nielsr/dino_deits8 | 15 | null | transformers | 9,554 | Entry not found |
orzhan/t5-long-extract | 9b20f3c309b8cbea80d2609bbd5a638d1c7a7385 | 2022-06-11T07:20:59.000Z | [
"pytorch",
"t5",
"feature-extraction",
"transformers"
] | feature-extraction | false | orzhan | null | orzhan/t5-long-extract | 15 | null | transformers | 9,555 | T5-small model fine-tuned for extractive summarization on long documents.
Repository: [GitHub](https://github.com/orzhan/t5-long-extract) |
patrickvonplaten/hf-reformer-crime-and-punish | 498eddd2421bd1902a147e550ffae000d7a60d55 | 2020-05-11T11:10:52.000Z | [
"pytorch",
"reformer",
"text-generation",
"transformers"
] | text-generation | false | patrickvonplaten | null | patrickvonplaten/hf-reformer-crime-and-punish | 15 | null | transformers | 9,556 | Entry not found |
patrickvonplaten/wav2vec2-common_voice-tr-demo | 59074c9bbe282a9c02a6422082d16fcc4aa46307 | 2021-12-20T12:54:39.000Z | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"speech-recognition",
"common_voice",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | false | patrickvonplaten | null | patrickvonplaten/wav2vec2-common_voice-tr-demo | 15 | null | transformers | 9,557 | ---
language:
- tr
license: apache-2.0
tags:
- speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-common_voice-tr-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
shoul... |
peggyhuang/bert-base-uncased-coqa | ae54d05fa6b4c7b6c04a9cd28c1fd26bfd23d4fa | 2021-11-19T09:05:00.000Z | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | false | peggyhuang | null | peggyhuang/bert-base-uncased-coqa | 15 | null | transformers | 9,558 | Entry not found |
pinecone/bert-retriever-squad2 | edb4465f3fc105473bf54cb7d4674d0d043d9185 | 2022-01-03T02:38:02.000Z | [
"pytorch",
"bert",
"feature-extraction",
"sentence-transformers",
"sentence-similarity",
"transformers"
] | sentence-similarity | false | pinecone | null | pinecone/bert-retriever-squad2 | 15 | null | sentence-transformers | 9,559 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluster... |
pkushiqiang/bert-title-org | 113cf90e11c9920cc55c2a885813d30166991300 | 2022-02-28T06:16:37.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | pkushiqiang | null | pkushiqiang/bert-title-org | 15 | null | transformers | 9,560 | Entry not found |
pmthangk09/bert-base-uncased-superglue-multirc | 5b503587b2e7cee15046475079d14a13aff1e616 | 2021-05-20T02:50:34.000Z | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | pmthangk09 | null | pmthangk09/bert-base-uncased-superglue-multirc | 15 | null | transformers | 9,561 | Entry not found |
pszemraj/t5-base-askscience | a7582c22c55096ed39fe3261852d94d767e1da98 | 2022-02-19T22:50:18.000Z | [
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:eli5",
"transformers",
"qa",
"askscience",
"lfqa",
"information retrieval",
"autotrain_compatible"
] | text2text-generation | false | pszemraj | null | pszemraj/t5-base-askscience | 15 | null | transformers | 9,562 | ---
language:
- en
tags:
- t5
- qa
- askscience
- lfqa
- information retrieval
datasets:
- eli5
metrics:
- rouge
widget:
- text: "why aren't there more planets in our solar system?"
example_title: "solar system"
- text: "question: what is a probability distribution? context: I am just learning about statistics."
e... |
racai/distilbert-multi-base-romanian-cased | 099fba005eedaeda5a4aabcf6e502c2df50f58db | 2021-12-24T17:32:28.000Z | [
"pytorch",
"tf",
"jax",
"distilbert",
"ro",
"dataset:oscar",
"dataset:wikipedia",
"arxiv:2112.12650",
"transformers",
"license:mit"
] | null | false | racai | null | racai/distilbert-multi-base-romanian-cased | 15 | null | transformers | 9,563 | ---
language: ro
license: mit
datasets:
- oscar
- wikipedia
---
# Romanian DistilBERT
This repository contains the a Romanian cased version of DistilBERT (named DistilMulti-BERT-base-ro in the paper) that was obtained by distilling an ensemble of two teacher models: [dumitrescustefan/bert-base-romanian-cased-v1](http... |
ramybaly/ner_conll2003 | 8705927627b7f05803a0a150c8c369c376ad1383 | 2021-08-21T03:21:14.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | false | ramybaly | null | ramybaly/ner_conll2003 | 15 | null | transformers | 9,564 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model_index:
- name: ner_conll2003
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
args: conll2... |
rebeccakoganlee/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ner | badcc7e3abb95def4e8dac5fc7bb5610b6c8e865 | 2021-11-23T20:42:01.000Z | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | rebeccakoganlee | null | rebeccakoganlee/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ner | 15 | null | transformers | 9,565 | Entry not found |
sarahmiller137/distilbert-base-uncased-ft-conll2003 | 97f129c62514a7e0aa79f6c8de00c17c792065a4 | 2022-07-14T11:52:53.000Z | [
"pytorch",
"distilbert",
"token-classification",
"en",
"dataset:conll2003",
"transformers",
"token classification",
"license:cc",
"model-index",
"autotrain_compatible"
] | token-classification | false | sarahmiller137 | null | sarahmiller137/distilbert-base-uncased-ft-conll2003 | 15 | null | transformers | 9,566 | ---
language:
- en
thumbnail: url to a thumbnail used in social sharing
tags:
- token classification
license: cc
datasets:
- conll2003
model-index:
- name: sarahmiller137/distilbert-base-uncased-ft-conll2003
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: ... |
sentence-transformers/distilroberta-base-msmarco-v1 | b625c1f869c7869b660b456ecf8eff290d1333e3 | 2022-06-16T01:04:36.000Z | [
"pytorch",
"tf",
"roberta",
"feature-extraction",
"arxiv:1908.10084",
"sentence-transformers",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | sentence-similarity | false | sentence-transformers | null | sentence-transformers/distilroberta-base-msmarco-v1 | 15 | null | sentence-transformers | 9,567 | ---
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... |
sismetanin/sbert-ru-sentiment-rutweetcorp | b7f3c2cea37655f012af16fc852c454f3f998e64 | 2021-05-20T06:41:48.000Z | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | false | sismetanin | null | sismetanin/sbert-ru-sentiment-rutweetcorp | 15 | null | transformers | 9,568 | Entry not found |
skplanet/dialog-koelectra-small-discriminator | d7a060551ecc231b35236a8d7d1647876c193986 | 2021-04-13T01:15:27.000Z | [
"pytorch",
"electra",
"pretraining",
"transformers"
] | null | false | skplanet | null | skplanet/dialog-koelectra-small-discriminator | 15 | null | transformers | 9,569 | # Dialog-KoELECTRA
Github : [https://github.com/skplanet/Dialog-KoELECTRA](https://github.com/skplanet/Dialog-KoELECTRA)
## Introduction
**Dialog-KoELECTRA** is a language model specialized for dialogue. It was trained with 22GB colloquial and written style Korean text data. Dialog-ELECTRA model is made based on the... |
spencerh/leftpartisan | 9cb2baaa91cdf3c9982ddced7c076550d9c32739 | 2021-04-23T19:27:15.000Z | [
"pytorch",
"tf",
"distilbert",
"text-classification",
"transformers"
] | text-classification | false | spencerh | null | spencerh/leftpartisan | 15 | null | transformers | 9,570 | # Text classifier using DistilBERT to determine Partisanship
## This is one of many single-class partisanship models
label_0 refers to "left" while label_1 refers to "other".
This model was trained on 40,000 articles.
### Best Practices
This model was optimized for 512 token-length text. Any text below 150 tokens... |
superb/wav2vec2-large-superb-er | bd13d8ed2b396e23676111aacff32283c9dece5d | 2021-11-04T16:03:41.000Z | [
"pytorch",
"wav2vec2",
"audio-classification",
"en",
"dataset:superb",
"arxiv:2105.01051",
"transformers",
"speech",
"audio",
"license:apache-2.0"
] | audio-classification | false | superb | null | superb/wav2vec2-large-superb-er | 15 | null | transformers | 9,571 | ---
language: en
datasets:
- superb
tags:
- speech
- audio
- wav2vec2
- audio-classification
license: apache-2.0
widget:
- example_title: IEMOCAP clip "happy"
src: https://cdn-media.huggingface.co/speech_samples/IEMOCAP_Ses01F_impro03_F013.wav
- example_title: IEMOCAP clip "neutral"
src: https://cdn-media.huggingfa... |
tbrasil/classificador_de_atendimento_2_classes_v1.1 | 147ae7455fb7891fbcef6e27de67badb01055d22 | 2021-08-02T17:51:56.000Z | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | false | tbrasil | null | tbrasil/classificador_de_atendimento_2_classes_v1.1 | 15 | null | transformers | 9,572 | Entry not found |
textattack/albert-base-v2-snli | 706e88d23c4ec5a68fbff2c1517d0da6ef7287d1 | 2020-07-06T16:36:47.000Z | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | false | textattack | null | textattack/albert-base-v2-snli | 15 | null | transformers | 9,573 | ## TextAttack Model Card
This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack
and the snli dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 64, a learning
rate of 2e-05, and a maximum sequence length of 64.
Since this was a classif... |
tmills/roberta_sfda_sharpseed | 10d59130d9a12a683c1049a7573848ccc020ea1e | 2021-05-20T22:41:21.000Z | [
"pytorch",
"jax",
"roberta",
"text-classification",
"transformers"
] | text-classification | false | tmills | null | tmills/roberta_sfda_sharpseed | 15 | null | transformers | 9,574 | Entry not found |
ttop324/kogpt2jnovel | 70c6af4eba91fb32a746588fc52c33c82437c58a | 2021-11-11T07:38:14.000Z | [
"pytorch",
"gpt2",
"text-generation",
"ko",
"transformers",
"license:cc-by-nc-sa-4.0"
] | text-generation | false | ttop324 | null | ttop324/kogpt2jnovel | 15 | null | transformers | 9,575 | ---
language: ko
tags:
- gpt2
license: cc-by-nc-sa-4.0
---
korean translated japan web novel finetuned from skt/kogpt2-base-v2 |
uclanlp/plbart-single_task-all-summarization | 486692f974ac352601f3952a154d9aa9fa4bb7de | 2022-03-02T07:28:07.000Z | [
"pytorch",
"plbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | uclanlp | null | uclanlp/plbart-single_task-all-summarization | 15 | null | transformers | 9,576 | Entry not found |
ufal/byt5-small-multilexnorm2021-hr | c98026c96146a7d3d920dc64bf082f97f1900027 | 2021-10-20T12:27:34.000Z | [
"pytorch",
"t5",
"text2text-generation",
"hr",
"dataset:mc4",
"dataset:wikipedia",
"dataset:multilexnorm",
"arxiv:2105.13626",
"arxiv:1907.06292",
"transformers",
"lexical normalization",
"license:apache-2.0",
"autotrain_compatible"
] | text2text-generation | false | ufal | null | ufal/byt5-small-multilexnorm2021-hr | 15 | null | transformers | 9,577 | ---
language: hr
datasets:
- mc4
- wikipedia
- multilexnorm
tags:
- lexical normalization
license: apache-2.0
---
# Fine-tuned ByT5-small for MultiLexNorm (Croatian version)
This is the official release of the fine-tuned models for ... |
unicamp-dl/ptt5-large-t5-vocab | c213b7615a0ecd776dfe6f2d95fcaca06fd03647 | 2021-06-23T14:32:15.000Z | [
"pytorch",
"tf",
"t5",
"text2text-generation",
"pt",
"dataset:brWaC",
"transformers",
"tensorflow",
"pt-br",
"license:mit",
"autotrain_compatible"
] | text2text-generation | false | unicamp-dl | null | unicamp-dl/ptt5-large-t5-vocab | 15 | null | transformers | 9,578 | ---
language: pt
license: mit
tags:
- t5
- pytorch
- tensorflow
- pt
- pt-br
datasets:
- brWaC
widget:
- text: "Texto de exemplo em português"
inference: false
---
# Portuguese T5 (aka "PTT5")
## Introduction
PTT5 is a T5 model pretrained in the BrWac corpus, a large collection of web pages in Portuguese, improvi... |
vasudevgupta/bigbird-pegasus-large-pubmed | 5cb34a36cccf14bb7bed607bade700d74e923fc2 | 2021-05-04T11:12:55.000Z | [
"pytorch",
"bigbird_pegasus",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | false | vasudevgupta | null | vasudevgupta/bigbird-pegasus-large-pubmed | 15 | null | transformers | 9,579 | Moved here: https://huggingface.co/google/bigbird-pegasus-large-pubmed |
vukpetar/trocr-small-photomath | daa6f7cd6b80a9040ddb2ca4f15061652d2068cc | 2021-12-27T19:41:43.000Z | [
"pytorch",
"vision-encoder-decoder",
"arxiv:2109.10282",
"transformers"
] | null | false | vukpetar | null | vukpetar/trocr-small-photomath | 15 | null | transformers | 9,580 | ## TrOCR (small-sized model, fine-tuned on Synthetic Math Expression Dataset)
TrOCR model fine-tuned on the Synthetic Math Expression Dataset. It was introduced in the paper [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://arxiv.org/abs/2109.10282) by Li et al. and first released... |
yazdipour/text-to-sparql-t5-small | f485542939bc21807227d766ecbb8e47007c989d | 2021-10-19T11:17:46.000Z | [
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | yazdipour | null | yazdipour/text-to-sparql-t5-small | 15 | null | transformers | 9,581 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- null
metrics:
- f1
model-index:
- name: text-to-sparql-t5-small-2021-10-19_10-17_lastDS
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
metrics:
- name: F1
type: f1
value: 0.31... |
yuvraj/xSumm | 6403af6f8f4eaf246bc94eef9d4ec1df88e2eca9 | 2020-12-11T22:05:01.000Z | [
"pytorch",
"bart",
"text2text-generation",
"en",
"transformers",
"summarization",
"extreme summarization",
"autotrain_compatible"
] | summarization | false | yuvraj | null | yuvraj/xSumm | 15 | null | transformers | 9,582 | ---
language: "en"
tags:
- summarization
- extreme summarization
---
## Model description
BartForConditionalGenerationModel for extreme summarization- creates a one line abstractive summary of a given article
## How to use
PyTorch model available
```python
from transformers import AutoTokenizer, AutoModelWith... |
zhiheng-huang/bert-large-uncased-whole-word-masking-embedding-relative-key-query | 8e5156c80b48db5fbe0868ca18d4e4e462a896b0 | 2021-05-20T09:48:50.000Z | [
"pytorch",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | false | zhiheng-huang | null | zhiheng-huang/bert-large-uncased-whole-word-masking-embedding-relative-key-query | 15 | null | transformers | 9,583 | Entry not found |
Davlan/xlm-roberta-base-masakhaner | 643ee144abafa9c5fbe5f71f25d8a0118b6344a3 | 2022-02-25T15:23:22.000Z | [
"pytorch",
"xlm-roberta",
"token-classification",
"am",
"ha",
"ig",
"rw",
"lg",
"luo",
"pcm",
"sw",
"wo",
"yo",
"multilingual",
"dataset:masakhaner",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | false | Davlan | null | Davlan/xlm-roberta-base-masakhaner | 15 | null | transformers | 9,584 | Hugging Face's logo
---
language:
- am
- ha
- ig
- rw
- lg
- luo
- pcm
- sw
- wo
- yo
- multilingual
datasets:
- masakhaner
---
# xlm-roberta-base-masakhaner
## Model description
**xlm-roberta-base-masakhaner** is the first **Named Entity Recognition** model for 10 African languages (Amharic, Hausa, Igbo, Kinyarwand... |
ghadeermobasher/BC5CDR-Chem2-imbalanced-BiomedNLP-PubMedBERT-base-uncased-abstract | a95c14a635a2938902dc6d864e6b1fb147e1faa9 | 2022-03-01T06:00:08.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC5CDR-Chem2-imbalanced-BiomedNLP-PubMedBERT-base-uncased-abstract | 15 | null | transformers | 9,585 | Entry not found |
ghadeermobasher/Model_org | ec0a976a03a68831924a915e003e3cbe8eee4ee6 | 2022-03-01T21:25:54.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_org | 15 | null | transformers | 9,586 | Entry not found |
ghadeermobasher/Model_imb | e01715bfd053cf8e19121f5b09131f2e2394a1ee | 2022-03-01T21:26:51.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_imb | 15 | null | transformers | 9,587 | Entry not found |
ghadeermobasher/Model_imb_1 | 1a90a396146a91d18e13ceae7a50bb42962c0250 | 2022-03-02T04:10:59.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_imb_1 | 15 | null | transformers | 9,588 | Entry not found |
ghadeermobasher/Model_org_1 | 9925b3108d651f35452c969d7289aca4d75f6ab1 | 2022-03-02T04:16:51.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_org_1 | 15 | null | transformers | 9,589 | Entry not found |
ghadeermobasher/Model_imb_2 | 4fdc981bc5a81f8d794ab339886b2630f0d7b089 | 2022-03-02T11:34:17.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_imb_2 | 15 | null | transformers | 9,590 | Entry not found |
ghadeermobasher/Model_co_imb | d4dcc81191114c756cac56ba59b7babe3d471a85 | 2022-03-01T23:08:18.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/Model_co_imb | 15 | null | transformers | 9,591 | Entry not found |
ActivationAI/distilbert-base-uncased-finetuned-emotion | dbf4470880ff3b73f22975241cd309bdf8e2195f | 2022-03-02T03:40:08.000Z | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | false | ActivationAI | null | ActivationAI/distilbert-base-uncased-finetuned-emotion | 15 | null | transformers | 9,592 | ---
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... |
ghadeermobasher/BC4-original-PubmedBert | 96d1e5c0b00169c4644306ddfd91da3dbe509f69 | 2022-03-03T02:53:18.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4-original-PubmedBert | 15 | null | transformers | 9,593 | Entry not found |
ghadeermobasher/BC4-original-PubmedBert_small | f72da94ac4f4208739edfaca46482bd43873f66f | 2022-03-02T11:07:21.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4-original-PubmedBert_small | 15 | null | transformers | 9,594 | Entry not found |
ghadeermobasher/BC4-modified-PubmedBert_small | c7ffad75406d8918820a2a813bca1e9e6a013c60 | 2022-03-02T11:07:25.000Z | [
"pytorch",
"tensorboard",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | false | ghadeermobasher | null | ghadeermobasher/BC4-modified-PubmedBert_small | 15 | null | transformers | 9,595 | Entry not found |
ivanlau/distil-bert-uncased-finetuned-github-issues | 0d35383caff319649c8996504a0f8b5b0a33dea4 | 2022-03-04T10:16:47.000Z | [
"pytorch",
"distilbert",
"text-classification",
"dataset:ticket tagger",
"transformers",
"model-index"
] | text-classification | false | ivanlau | null | ivanlau/distil-bert-uncased-finetuned-github-issues | 15 | null | transformers | 9,596 | ---
datasets:
- ticket tagger
metrics:
- accuracy
model-index:
- name: distil-bert-uncased-finetuned-github-issues
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: ticket tagger
type: ticket tagger
args: full
metrics:
- name: Accuracy
... |
l3cube-pune/marathi-albert-v2 | 76ef3b6421baf9bb747e102310594550f4627587 | 2022-06-26T15:13:43.000Z | [
"pytorch",
"albert",
"fill-mask",
"mr",
"dataset:L3Cube-MahaCorpus",
"arxiv:2202.01159",
"transformers",
"license:cc-by-4.0",
"autotrain_compatible"
] | fill-mask | false | l3cube-pune | null | l3cube-pune/marathi-albert-v2 | 15 | 1 | transformers | 9,597 | ---
license: cc-by-4.0
language: mr
datasets:
- L3Cube-MahaCorpus
---
## MahaAlBERT
MahaAlBERT is a Marathi AlBERT model trained on L3Cube-MahaCorpus and other publicly available Marathi monolingual datasets.
[dataset link] (https://github.com/l3cube-pune/MarathiNLP)
More details on the dataset, models, and baseline... |
timothyshi/bart-large-cnn-finetuned-booksum-chapter | 24ef62670565e5ca800a0c4365d7db48bea3f494 | 2022-03-07T05:13:01.000Z | [
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"license:mit",
"model-index",
"autotrain_compatible"
] | text2text-generation | false | timothyshi | null | timothyshi/bart-large-cnn-finetuned-booksum-chapter | 15 | 1 | transformers | 9,598 | ---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-booksum-chapter
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 ... |
datarpit/toy | 9ffd6ea55f01c2da71bfd7f7a3c6c5a3f5472cdb | 2022-03-10T00:06:22.000Z | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | question-answering | false | datarpit | null | datarpit/toy | 15 | null | transformers | 9,599 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: toy
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. -->
# toy
This model is a fine-tuned... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.