# Social Media Text

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

A multilingual sentiment analysis model based on the XLM-RoBERTa architecture, specifically optimized for German, achieving an 87% F1 score in German sentiment analysis tasks.

The first open-source large language model with instruction-following capability for explainable mental health analysis, fine-tuned based on LLaMA2-chat-7B

A Japanese sentiment analysis model fine-tuned from Luke-japanese-large-lite, capable of identifying eight types of emotions in text

A sentiment analysis model based on the IndoBERT pre-trained model for predicting six types of emotions in Indonesian sentences.

A financial social media sentiment analysis model fine-tuned on DistilBERT, specialized in analyzing text sentiment from platforms like StockTwits

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 French tweet sentiment classification model fine-tuned based on Yanzhu/bertweetfr-base, specifically designed for analyzing sentiment tendencies in COVID-19-related tweets.