| --- |
| license: mit |
| --- |
| # **XLM-R-Large-Tweet** |
|
|
| **XLM-R-Large-Tweet** is a version of the [XLM-R-Large-Tweet-Base]( https://huggingface.co/DarijaM/XLM-R-Large-Tweet-base)*, fine-tuned for sentiment analysis using 5,610 annotated Serbian COVID-19 vaccination-related tweets. |
| Specifically, it is tailored for **five-class sentiment analysis** to capture finer sentiment nuances in the social media domain using the following scale: very negative, negative, neutral, positive, and very positive. |
| |
| **XLM-R-Large-Tweet-Base is an additionally pretrained version of the [XLM-RoBERTa large-sized model](https://huggingface.co/FacebookAI/xlm-roberta-large).* |
| |
| ## How to Use |
| To use the model, you can load it with the following code: |
| |
| ```python |
| from transformers import AutoTokenizer, XLMRobertaForSequenceClassification |
| |
| model_name = "DarijaM/XLM-R-Large-Tweet" |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = XLMRobertaForSequenceClassification.from_pretrained(model_name) |
