modelId stringlengths 6 107 | label list | readme stringlengths 0 56.2k | readme_len int64 0 56.2k |
|---|---|---|---|
rohanrajpal/bert-base-codemixed-uncased-sentiment | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ---
language:
- hi
- en
tags:
- hi
- en
- codemix
datasets:
- SAIL 2017
---
# Model name
## Model description
I took a bert-base-multilingual-cased model from huggingface and finetuned it on SAIL 2017 dataset.
## Intended uses & limitations
#### How to use
```python
# You can include sample code which will be f... | 1,326 |
Jeevesh8/std_0pnt2_bert_ft_cola-53 | null | Entry not found | 15 |
mujeensung/roberta-base_mnli_bc | [
"contradiction",
"entailment",
"neutral"
] | ---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: roberta-base_mnli_bc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name:... | 1,749 |
Jeevesh8/std_0pnt2_bert_ft_cola-54 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-55 | null | Entry not found | 15 |
razent/SciFive-base-Pubmed_PMC | null | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
- pmc/open_access
---
# SciFive Pubmed+PMC Base
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs... | 1,404 |
has-abi/bert-finetuned-resumes-sections | [
"awards",
"certificates",
"contact/name/title",
"education",
"interests",
"languages",
"para",
"professional_experiences",
"projects",
"skills",
"soft_skills",
"summary"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-finetuned-resumes-sections
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 c... | 2,374 |
jy46604790/Fake-News-Bert-Detect | null | ---
license: apache-2.0
---
# Fake News Recognition
## Overview
This model is trained by over 40,000 news from different medias based on the 'roberta-base'. It can give result by simply entering the text of the news less than 500 words(the excess will be truncated automatically).
LABEL_0: Fake news
LABEL_1: Real... | 2,136 |
Jeevesh8/std_0pnt2_bert_ft_cola-56 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-57 | null | Entry not found | 15 |
sismetanin/rubert-toxic-pikabu-2ch | null | ---
language:
- ru
tags:
- toxic comments classification
---
## RuBERT-Toxic
RuBERT-Toxic is a [RuBERT](https://huggingface.co/DeepPavlov/rubert-base-cased) model fine-tuned on [Kaggle Russian Language Toxic Comments Dataset](https://www.kaggle.com/blackmoon/russian-language-toxic-comments). You can find a detailed ... | 2,179 |
NDugar/ZSD-microsoft-v2xxlmnli | [
"CONTRADICTION",
"NEUTRAL",
"ENTAILMENT"
] | ---
language: en
tags:
- deberta-v1
- deberta-mnli
tasks: mnli
thumbnail: https://huggingface.co/front/thumbnails/microsoft.png
license: mit
pipeline_tag: zero-shot-classification
---
## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
[DeBERTa](https://arxiv.org/abs/2006.03654) improves the BERT and RoBERT... | 3,876 |
Raychanan/bert-base-chinese-FineTuned-Binary-Best | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-58 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-59 | null | Entry not found | 15 |
DaNLP/da-bert-tone-subjective-objective | [
"objective",
"subjective"
] | ---
language:
- da
tags:
- bert
- pytorch
- subjectivity
- objectivity
license: cc-by-sa-4.0
datasets:
- Twitter Sentiment
- Europarl Sentiment
widget:
- text: Jeg tror alligvel, det bliver godt
metrics:
- f1
---
# Danish BERT Tone for the detection of subjectivity/objectivity
The BERT Tone model detects whether a te... | 1,224 |
barissayil/bert-sentiment-analysis-sst | null | Entry not found | 15 |
cardiffnlp/twitter-roberta-base-emoji | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_12",
"LABEL_13",
"LABEL_14",
"LABEL_15",
"LABEL_16",
"LABEL_17",
"LABEL_18",
"LABEL_19",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | # Twitter-roBERTa-base for Emoji prediction
This is a roBERTa-base model trained on ~58M tweets and finetuned for emoji prediction with the TweetEval benchmark.
- Paper: [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf).
- Git Repo: [Tweeteval official repository](https://github.... | 2,625 |
Jeevesh8/std_0pnt2_bert_ft_cola-60 | null | Entry not found | 15 |
DaNLP/da-bert-hatespeech-detection | [
"not offensive",
"offensive"
] | ---
language:
- da
tags:
- bert
- pytorch
- hatespeech
license: cc-by-sa-4.0
datasets:
- social media
metrics:
- f1
widget:
- text: "Senile gamle idiot"
---
# Danish BERT for hate speech (offensive language) detection
The BERT HateSpeech model detects whether a Danish text is offensive or not.
It is based on the pre... | 1,049 |
Jeevesh8/std_0pnt2_bert_ft_cola-61 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-63 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-64 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-62 | null | Entry not found | 15 |
abhishek/autonlp-japanese-sentiment-59363 | [
"negative",
"positive"
] | ---
tags: autonlp
language: ja
widget:
- text: "🤗AutoNLPが大好きです"
datasets:
- abhishek/autonlp-data-japanese-sentiment
---
# Model Trained Using AutoNLP
- Problem type: Binary Classification
- Model ID: 59363
## Validation Metrics
- Loss: 0.12651239335536957
- Accuracy: 0.9532079853817648
- Precision: 0.972968827882... | 1,094 |
ShreyaR/finetuned-roberta-depression | null | ---
license: mit
tags:
- generated_from_trainer
widget:
- text: "I feel so low and numb, don't feel like doing anything. Just passing my days"
- text: "Sleep is my greatest and most comforting escape whenever I wake up these days. The literal very first emotion I feel is just misery and reminding myself of all my probl... | 1,961 |
Jeevesh8/std_0pnt2_bert_ft_cola-66 | null | Entry not found | 15 |
gchhablani/bert-base-cased-finetuned-mrpc | [
"equivalent",
"not_equivalent"
] | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
- fnet-bert-base-comparison
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: bert-base-cased-finetuned-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
ty... | 3,053 |
cross-encoder/ms-marco-TinyBERT-L-4 | [
"LABEL_0"
] | ---
license: apache-2.0
---
# Cross-Encoder for MS Marco
This model was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch).... | 3,233 |
lordtt13/emo-mobilebert | [
"angry",
"happy",
"others",
"sad"
] | ---
language: en
datasets:
- emo
---
## Emo-MobileBERT: a thin version of BERT LARGE, trained on the EmoContext Dataset from scratch
### Details of MobileBERT
The **MobileBERT** model was presented in [MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices](https://arxiv.org/abs/2004.02984) by *Zhiqin... | 2,933 |
textattack/roberta-base-RTE | null | ## TextAttack Model Card
This `roberta-base` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 16, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this was a classifi... | 618 |
daveni/twitter-xlm-roberta-emotion-es | [
"anger",
"disgust",
"fear",
"joy",
"others",
"sadness",
"surprise"
] | ---
language:
- es
tags:
- Emotion Analysis
---
**Note**: This model & model card are based on the [finetuned XLM-T for Sentiment Analysis](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment)
# twitter-XLM-roBERTa-base for Emotion Analysis
This is a XLM-roBERTa-base model trained on ~198M tweets ... | 3,814 |
manishiitg/distilbert-resume-parts-classify | [
"LABEL_0",
"LABEL_1",
"LABEL_10",
"LABEL_11",
"LABEL_2",
"LABEL_3",
"LABEL_4",
"LABEL_5",
"LABEL_6",
"LABEL_7",
"LABEL_8",
"LABEL_9"
] | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-65 | null | Entry not found | 15 |
cross-encoder/quora-roberta-base | [
"LABEL_0"
] | ---
license: apache-2.0
---
# Cross-Encoder for Quora Duplicate Questions Detection
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.
## Training Data
This model was trained on the [Quora Duplicate Questi... | 1,070 |
Jeevesh8/std_0pnt2_bert_ft_cola-68 | null | Entry not found | 15 |
Jeevesh8/std_0pnt2_bert_ft_cola-67 | null | Entry not found | 15 |
symanto/xlm-roberta-base-snli-mnli-anli-xnli | [
"ENTAILMENT",
"NEUTRAL",
"CONTRADICTION"
] | ---
language:
- ar
- bg
- de
- el
- en
- es
- fr
- ru
- th
- tr
- ur
- vn
- zh
datasets:
- SNLI
- MNLI
- ANLI
- XNLI
tags:
- zero-shot-classification
---
A cross-attention NLI model trained for zero-shot and few-shot text classification.
The base model is [xlm-roberta-base](https://hugging... | 1,690 |
Jeevesh8/std_0pnt2_bert_ft_cola-70 | null | Entry not found | 15 |
bhadresh-savani/albert-base-v2-emotion | [
"anger",
"fear",
"joy",
"love",
"sadness",
"surprise"
] | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- emotion
- pytorch
license: apache-2.0
datasets:
- emotion
metrics:
- Accuracy, F1 Score
---
# Albert-base-v2-emotion
## Model description:
[Albert](https:/... | 2,634 |
jason9693/SoongsilBERT-base-beep | [
"hate",
"none",
"offensive"
] | ---
language: ko
widget:
- text: "응 어쩔티비~"
datasets:
- kor_hate
---
# Finetuning
## Result
### Base Model
| | Size | **NSMC**<br/>(acc) | **Naver NER**<br/>(F1) | **PAWS**<br/>(acc) | **KorNLI**<br/>(acc) | **KorSTS**<br/>(spearman) | **Question Pair**<br/>(acc) | **KorQuaD (Dev)**<br/>(EM/F1... | 3,679 |
Jeevesh8/std_0pnt2_bert_ft_cola-69 | null | Entry not found | 15 |
nateraw/bert-base-uncased-ag-news | [
"Business",
"Sci/Tech",
"Sports",
"World"
] | ---
language:
- en
thumbnail: https://avatars3.githubusercontent.com/u/32437151?s=460&u=4ec59abc8d21d5feea3dab323d23a5860e6996a4&v=4
tags:
- text-classification
- ag_news
- pytorch
license: mit
datasets:
- ag_news
metrics:
- accuracy
---
# bert-base-uncased-ag-news
## Model description
`bert-base-uncased` finetuned ... | 787 |
Jeevesh8/std_0pnt2_bert_ft_cola-72 | null | Entry not found | 15 |
IlyaGusev/xlm_roberta_large_headline_cause_full | [
"bad",
"same",
"rel",
"left_right_cause",
"right_left_cause",
"left_right_refute",
"right_left_refute"
] | ---
language:
- ru
- en
tags:
- xlm-roberta-large
datasets:
- IlyaGusev/headline_cause
license: apache-2.0
widget:
- text: "Песков опроверг свой перевод на удаленку</s>Дмитрий Песков перешел на удаленку"
---
# XLM-RoBERTa HeadlineCause Full
## Model description
This model was trained to predict the presence of caus... | 3,246 |
poom-sci/WangchanBERTa-finetuned-sentiment | [
"neg",
"neu",
"pos"
] | ---
language:
- th
tags:
- sentiment-analysis
license: apache-2.0
datasets:
- wongnai_reviews
- wisesight_sentiment
- generated_reviews_enth
widget:
- text: "โอโห้ ช่องนี้เปิดโลกเรามากเลยค่ะ คือตอนช่วงหาคำตอบเรานี่อึ้งไปเลย ดูจีเนียสมากๆๆ"
example_title: "Positive"
- text: "เริ่มจากชายเน็ตคนหนึ่งเปิดประเด็นว่าไปพบเจ้... | 551 |
HooshvareLab/bert-fa-base-uncased-sentiment-snappfood | [
"HAPPY",
"SAD"
] | ---
language: fa
license: apache-2.0
---
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](... | 2,650 |
cointegrated/rubert-tiny-bilingual-nli | [
"entailment",
"not_entailment"
] | ---
language: ru
pipeline_tag: zero-shot-classification
tags:
- rubert
- russian
- nli
- rte
- zero-shot-classification
widget:
- text: "Сервис отстойный, кормили невкусно"
candidate_labels: "Мне понравилось, Мне не понравилось"
hypothesis_template: "{}."
---
# RuBERT-tiny for NLI (natural language inference)
This... | 633 |
razent/SciFive-large-Pubmed_PMC | null | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
- pmc/open_access
---
# SciFive Pubmed+PMC Large
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/a... | 1,408 |
twigs/cwi-regressor | [
"LABEL_0"
] | Entry not found | 15 |
aychang/bert-base-cased-trec-coarse | [
"ABBR",
"DESC",
"ENTY",
"HUM",
"LOC",
"NUM"
] | ---
language:
- en
thumbnail:
tags:
- text-classification
license: mit
datasets:
- trec
metrics:
---
# bert-base-cased trained on TREC 6-class task
## Model description
A simple base BERT model trained on the "trec" dataset.
## Intended uses & limitations
#### How to use
##### Transformers
```python
# Load mod... | 2,246 |
svalabs/gbert-large-zeroshot-nli | [
"contradiction",
"entailment",
"neutral"
] | ---
language: German
tags:
- text-classification
- pytorch
- nli
- de
pipeline_tag: zero-shot-classification
widget:
- text: "Ich habe ein Problem mit meinem Iphone das so schnell wie möglich gelöst werden muss."
candidate_labels: "Computer, Handy, Tablet, dringend, nicht dringend"
hypothesis_template: ... | 3,670 |
Jeevesh8/std_0pnt2_bert_ft_cola-71 | null | Entry not found | 15 |
tomh/toxigen_roberta | null | ---
language:
- en
tags:
- text-classification
---
Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, Ece Kamar.
This model comes from the paper [ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection](https://arxiv.org/abs/2203.09509) and can... | 904 |
lvwerra/bert-imdb | null | # BERT-IMDB
## What is it?
BERT (`bert-large-cased`) trained for sentiment classification on the [IMDB dataset](https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews).
## Training setting
The model was trained on 80% of the IMDB dataset for sentiment classification for three epochs with a learning... | 619 |
Jeevesh8/std_0pnt2_bert_ft_cola-73 | null | Entry not found | 15 |
MoritzLaurer/DeBERTa-v3-xsmall-mnli-fever-anli-ling-binary | [
"entailment",
"not_entailment"
] | ---
language:
- en
tags:
- text-classification
- zero-shot-classification
metrics:
- accuracy
datasets:
- multi_nli
- anli
- fever
- lingnli
pipeline_tag: zero-shot-classification
---
# DeBERTa-v3-xsmall-mnli-fever-anli-ling-binary
## Model description
This model was trained on 782 357 hypothesis-premise pairs from 4... | 4,328 |
abhishek/autonlp-bbc-news-classification-37229289 | [
"business",
"entertainment",
"politics",
"sport",
"tech"
] | ---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- abhishek/autonlp-data-bbc-news-classification
co2_eq_emissions: 5.448567309047846
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 37229289
- CO2 Emissions (in grams): 5.448567309047846
## Validatio... | 1,425 |
Jeevesh8/std_0pnt2_bert_ft_cola-74 | null | Entry not found | 15 |
IDEA-CCNL/Erlangshen-MegatronBert-1.3B-Sentiment | null | ---
language:
- zh
license: apache-2.0
tags:
- bert
- NLU
- Sentiment
inference: true
widget:
- text: "今天心情不好"
---
# Erlangshen-MegatronBert-1.3B-Semtiment, model (Chinese)，one model of [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM).
We collect 8 sentiment datasets in the Chinese domain for fin... | 1,582 |
boychaboy/SNLI_distilbert-base-cased | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
Recognai/zeroshot_selectra_medium | [
"contradiction",
"neutral",
"entailment"
] | ---
language: es
tags:
- zero-shot-classification
- nli
- pytorch
datasets:
- xnli
pipeline_tag: zero-shot-classification
license: apache-2.0
widget:
- text: "El autor se perfila, a los 50 años de su muerte, como uno de los grandes de su siglo"
candidate_labels: "cultura, sociedad, economia, salud, deportes"
---
# Z... | 4,337 |
Jeevesh8/std_0pnt2_bert_ft_cola-75 | null | Entry not found | 15 |
cross-encoder/nli-deberta-base | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
pipeline_tag: zero-shot-classification
tags:
- deberta-base-base
datasets:
- multi_nli
- snli
metrics:
- accuracy
license: apache-2.0
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples... | 2,564 |
microsoft/DialogRPT-width | null | # Demo
Please try this [➤➤➤ Colab Notebook Demo (click me!)](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)
| Context | Response | `width` score |
| :------ | :------- | :------------: |
| I love NLP! | Can anyone recommend a nice review paper? | 0.701 |
| I love NLP! | ... | 2,607 |
Maklygin/mBert-relation-extraction-FT | null | Entry not found | 15 |
mmillet/distilrubert-tiny-2ndfinetune-epru | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-tiny-2ndfinetune-epru
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 re... | 2,288 |
ipuneetrathore/bert-base-cased-finetuned-finBERT | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ## FinBERT
Code for importing and using this model is available [here](https://github.com/ipuneetrathore/BERT_models)
| 119 |
Jeevesh8/std_0pnt2_bert_ft_cola-76 | null | Entry not found | 15 |
DTAI-KULeuven/robbert-v2-dutch-sentiment | [
"Negative",
"Positive"
] | ---
language: nl
license: mit
datasets:
- dbrd
model-index:
- name: robbert-v2-dutch-sentiment
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: dbrd
type: sentiment-analysis
split: test
metrics:
- name: Accuracy
type: accuracy
... | 4,294 |
Jeevesh8/std_0pnt2_bert_ft_cola-77 | null | Entry not found | 15 |
cardiffnlp/bertweet-base-emotion | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | 0 | |
valhalla/bart-large-sst2 | [
"NEGATIVE",
"POSITIVE"
] | Entry not found | 15 |
dmis-lab/biobert-large-cased-v1.1-mnli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
textattack/roberta-base-MRPC | null | ## TextAttack Model Card
This `roberta-base` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 16, a learning
rate of 3e-05, and a maximum sequence length of 256.
Since this was a classifi... | 618 |
mrm8488/bert-mini-finetuned-age_news-classification | [
"World",
"Sports",
"Business",
"Sci/Tech"
] | ---
language: en
tags:
- news
- classification
- mini
datasets:
- ag_news
widget:
- text: "Israel withdraws from Gaza camp Israel withdraws from Khan Younis refugee camp in the Gaza Strip, after a four-day operation that left 11 dead."
---
# BERT-Mini fine-tuned on age_news dataset for news classification
Test set ac... | 331 |
Jeevesh8/std_0pnt2_bert_ft_cola-78 | null | Entry not found | 15 |
Mithil/Bert | null | ---
license: afl-3.0
---
| 25 |
IMSyPP/hate_speech_en | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | ---
widget:
- text: "My name is Mark and I live in London. I am a postgraduate student at Queen Mary University."
language:
- en
license: mit
---
# Hate Speech Classifier for Social Media Content in English Language
A monolingual model for hate speech classification of social media content in English language. Th... | 802 |
snunlp/KR-FinBert-SC | [
"negative",
"neutral",
"positive"
] | ---
language:
- ko
---
# KR-FinBert & KR-FinBert-SC
Much progress has been made in the NLP (Natural Language Processing) field, with numerous studies showing that domain adaptation using small-scale corpus and fine-tuning with labeled data is effective for overall performance improvement.
we proposed KR-FinBert for... | 2,669 |
Jeevesh8/std_0pnt2_bert_ft_cola-79 | null | Entry not found | 15 |
IDEA-CCNL/Erlangshen-MegatronBert-1.3B-NLI | null | ---
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-MegatronBert-1.3B-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 Chi... | 1,596 |
cross-encoder/nli-MiniLM2-L6-H768 | [
"contradiction",
"entailment",
"neutral"
] | ---
language: en
pipeline_tag: zero-shot-classification
license: apache-2.0
tags:
- MiniLMv2
datasets:
- multi_nli
- snli
metrics:
- accuracy
---
# Cross-Encoder for Natural Language Inference
This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applicat... | 2,567 |
TransQuest/monotransquest-da-en_zh-wiki | [
"LABEL_0"
] | ---
language: en-zh
tags:
- Quality Estimation
- monotransquest
- DA
license: apache-2.0
---
# TransQuest: Translation Quality Estimation with Cross-lingual Transformers
The goal of quality estimation (QE) is to evaluate the quality of a translation without having access to a reference translation. High-accuracy QE t... | 5,401 |
eleldar/language-detection | [
"ar",
"bg",
"de",
"el",
"en",
"es",
"fr",
"hi",
"it",
"ja",
"nl",
"pl",
"pt",
"ru",
"sw",
"th",
"tr",
"ur",
"vi",
"zh"
] | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-language-detection
results: []
---
# Clone from [https://huggingface.co/papluca/xlm-roberta-base-language-detection](xlm-roberta-base-language-detection)
This model is a fine-tuned version of [xlm-roberta-... | 5,748 |
microsoft/DialogRPT-depth | null | # Demo
Please try this [➤➤➤ Colab Notebook Demo (click me!)](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)
| Context | Response | `depth` score |
| :------ | :------- | :------------: |
| I love NLP! | Can anyone recommend a nice review paper? | 0.724 |
| I love NLP! | ... | 2,634 |
dhtocks/Topic-Classification | [
"LABEL_0",
"LABEL_1",
"LABEL_2",
"LABEL_3"
] | Entry not found | 15 |
huggingface/distilbert-base-uncased-finetuned-mnli | [
"contradiction",
"entailment",
"neutral"
] | Entry not found | 15 |
Gunulhona/tbbcmodel | [
"Agitation",
"Changes in Appetite",
"Changes in Sleeping Pattern",
"Concentration Difficultiy",
"Crying",
"Gulity Feelings",
"Indecisivness",
"Irritability",
"Loss of Energy",
"Loss of Interest",
"Loss of Interest in Sex",
"Loss of Pleasure",
"Non BDI",
"Past Failure",
"Pessimism",
"Pu... | Entry not found | 15 |
Elron/bleurt-base-512 | [
"LABEL_0"
] | \n## BLEURT
Pytorch version of the original BLEURT models from ACL paper ["BLEURT: Learning Robust Metrics for Text Generation"](https://aclanthology.org/2020.acl-main.704/) by
Thibault Sellam, Dipanjan Das and Ankur P. Parikh of Google Research.
The code for model conversion was originated from [this notebook](http... | 999 |
Gunulhona/tbnymodel | [
"Negative",
"Non Related",
"Positive"
] | Entry not found | 15 |
Gunulhona/tbecmodel | [
"ANGER",
"DISGUST",
"FEAR",
"HAPPINESS",
"NEUTRALITY",
"SADNESS",
"SURPRISED"
] | Entry not found | 15 |
valurank/distilroberta-news-small | [
"bad",
"good",
"medium"
] | ---
license: other
language: en
datasets:
- valurank/news-small
---
# DistilROBERTA fine-tuned for news classification
This model is based on [distilroberta-base](https://huggingface.co/distilroberta-base) pretrained weights, with a classification head fine-tuned to classify news articles into 3 categories (bad, medi... | 618 |
Seethal/sentiment_analysis_generic_dataset | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | ## BERT base model (uncased)
Pretrained model on English language using a masked language modeling (MLM) objective. This model is uncased: it does not make a difference between english and English.
## Model description
BERT is a transformers model pretrained on a large corpus of English data in a self-supervised fashi... | 1,988 |
textattack/bert-base-uncased-snli | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | Entry not found | 15 |
razent/SciFive-base-Pubmed | null | ---
language:
- en
tags:
- token-classification
- text-classification
- question-answering
- text2text-generation
- text-generation
datasets:
- pubmed
---
# SciFive Pubmed Base
## Introduction
Paper: [SciFive: a text-to-text transformer model for biomedical literature](https://arxiv.org/abs/2106.03598)
Authors... | 1,375 |
textattack/albert-base-v2-MRPC | null | ## TextAttack Model Card
This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack
and the glue dataset loaded using the `nlp` library. The model was fine-tuned
for 5 epochs with a batch size of 32, a learning
rate of 2e-05, and a maximum sequence length of 128.
Since this was a classi... | 620 |
HooshvareLab/bert-fa-base-uncased-clf-persiannews | [
"اجتماعی",
"اقتصادی",
"بین الملل",
"سیاسی",
"علمی فناوری",
"فرهنگی هنری",
"ورزشی",
"پزشکی"
] | ---
language: fa
license: apache-2.0
---
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT]... | 2,767 |
cardiffnlp/bertweet-base-sentiment | [
"LABEL_0",
"LABEL_1",
"LABEL_2"
] | 0 | |
assemblyai/distilbert-base-uncased-sst2 | null | # DistilBERT-Base-Uncased for Sentiment Analysis
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) originally released in ["DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter"](https://arxiv.org/abs/1910.01108) and trained on the [... | 1,779 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.