heydariAI

My Github: @heydaari My Linkedin: Mohammad Hassan Heydari This model is a fine-tuned version of xlm-roberta-base, specifically trained on a massive corpus of Persian data to create high-quality contextual embeddings for Persian sentences and paragraphs. It is designed to perform exceptionally well on tasks such as semantic search, clustering, and contextual similarity for Persian text, while also supporting multilingual tasks in English and Persian. The fine-tuning process focused on adapting the pre-trained multilingual XLM-RoBERTa model to better capture Persian linguistic nuances, making it highly effective for tasks requiring embeddings tailored to the Persian language. Using this model becomes easy when you have sentence-transformers installed: Usage (HuggingFace Transformers) Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.