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--- |
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license: mit |
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--- |
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# **XLM-R-Large-Tweet** |
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**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. |
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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. |
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**XLM-R-Large-Tweet-Base is an additionally pretrained version of the [XLM-RoBERTa large-sized model](https://huggingface.co/FacebookAI/xlm-roberta-large).* |
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## How to Use |
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To use the model, you can load it with the following code: |
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```python |
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from transformers import AutoTokenizer, XLMRobertaForSequenceClassification |
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model_name = "DarijaM/XLM-R-Large-Tweet" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = XLMRobertaForSequenceClassification.from_pretrained(model_name) |
