# Multilingual Sentiment Analysis

A multilingual sentiment analysis model based on DistilBERT, suitable for text sentiment classification tasks in multiple languages.

A multilingual sentiment analysis model based on XLM-RoBERTa, supporting AutoTrain for text classification tasks.

BERT-based multilingual sentiment classification model supporting text sentiment analysis in 6 languages

A multilingual sentiment classification model fine-tuned based on ModernBERT-large, supporting sentiment analysis in 16+ languages

This model is a multilingual sentiment analysis model fine-tuned on an unspecified dataset based on vinai/phobert-base, supporting sentiment classification tasks for multilingual texts including Vietnamese.

A multilingual sentiment classification model fine-tuned based on ModernBERT-base, supporting sentiment analysis for 16+ languages

Multilingual text sentiment evaluation model based on E5 small architecture

A multilingual sentiment analysis model fine-tuned based on DistilBERT, supporting 21 languages, suitable for various scenarios such as social media and customer feedback analysis.

A multilingual text sentiment classification model fine-tuned based on mDeBERTa-v3-base, supporting cross-language sentiment analysis

A Portuguese text processing model fine-tuned on 6.6 million sentence pairs and named entities, specializing in natural language understanding and generation tasks.

A fine-tuned BERT model for cross-lingual emotion classification based on the GoEmotions dataset, supporting English and Chinese texts, capable of classifying 28 emotion categories.

This is a multilingual sentiment analysis model trained using zero-shot distillation technology, supporting sentiment classification in 12 languages.

XLM-EMO is a multilingual sentiment analysis model fine-tuned based on the XLM-T model, supporting 19 languages and specifically designed for sentiment prediction in social media texts.

This is a multilingual text sentiment analysis model based on DistilBERT, fine-tuned on the amazon_reviews_multi dataset, supporting sentiment classification tasks in multiple languages.

A multilingual text sentiment analysis model based on DistilBERT, fine-tuned on the Amazon multilingual reviews dataset

A text classification model fine-tuned on the Amazon multilingual reviews dataset based on the roberta-base-bne model, primarily used for sentiment analysis of Spanish comments

This is a sentiment analysis model trained on a large-scale multilingual dataset of COVID19-related tweets, supporting sentiment classification in multiple languages.

A multilingual XLM-Roberta sequence classification model for text sentiment analysis, fine-tuned based on the sentiment classification model from the Cardiff NLP team.

A multilingual BERT-based model for classifying attitudes towards COVID-19 curfew measures in Belgian tweets

A multilingual sentiment analysis model based on XLM-RoBERTa, supporting English and Russian, specifically optimized for Twitter emoji sentiment analysis.

This model is used to analyze Belgian users' attitudes towards COVID-19 curfew policies, supporting sentiment classification for tweets in Dutch, French, and English.