# Multi-emotion Recognition
Distilbert Base Uncased Finetuned On Emotions Data
Apache-2.0
This model is a fine-tuned version of distilbert-base-uncased on an emotions dataset, designed for text sentiment classification.
Text Classification
Transformers

D
Shubhu07
25
1
Chinese Emotion Small
MIT
A Chinese sentiment classification model fine-tuned based on mDeBERTa-v3-base, capable of recognizing 8 emotion labels
Text Classification
Transformers Chinese

C
Johnson8187
10.58k
2
Chinese Emotion
MIT
Chinese sentiment classification model fine-tuned based on xlm-roberta-large-xnli, capable of recognizing 8 emotion labels
Text Classification
Transformers Chinese

C
Johnson8187
791
10
Distilbert Finetuned On Emotion
Apache-2.0
A text classification model fine-tuned on emotion datasets based on DistilBERT, used to identify emotional categories in text.
Text Classification
Transformers

D
Rahmat82
1,652
2
BERT Emotions Classifier
A BERT-based fine-tuned model designed for multi-label sentiment classification, supporting recognition of 11 emotions.
Text Classification
Transformers English

B
ayoubkirouane
2,661
15
Hebemo Surprise
HebEMO is a tool for detecting polarity and extracting emotions in modern Hebrew, trained on COVID-related datasets, and excels in polarity classification and emotion recognition tasks.
Text Classification
Transformers

H
avichr
119
0
Hebemo Trust
HebEMO is a tool designed to detect polarity and extract emotions from modern Hebrew user-generated content (UGC), trained on a unique COVID-19-related dataset.
Text Classification
Transformers

H
avichr
119
0
Hebemo Anger
HebEMO is a tool designed to detect sentiment polarity and extract emotions from modern Hebrew user-generated content (UGC), trained on a unique COVID-19 related dataset.
Text Classification
Transformers

H
avichr
117
0
Hebemo Fear
HebEMO is a tool designed to detect sentiment polarity and extract emotions from modern Hebrew user-generated content, trained on a unique COVID-19 related dataset with superior performance.
Text Classification
Transformers

H
avichr
111
1
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