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README.md

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 # Model Information
 
-XXXX is an updated version of [Mistral-7B-v0.2](https://huggingface.co/alpindale/Mistral-7B-v0.2-hf) specifically fine-tuned with SFT and LoRA adjustments.
+XXXXQuantized is a compact iteration of the model [XXXX](https://huggingface.co/MoxoffSpA/xxxx), optimized for efficiency.
+It is offered in two distinct configurations: a 4-bit version and an 8-bit version, each designed to maintain the model's effectiveness while significantly reducing its size.
+and computational requirements.
 
 - It's trained both on publicly available datasets, like [SQUAD-it](https://huggingface.co/datasets/squad_it), and datasets we've created in-house.
 - it's designed to understand and maintain context, making it ideal for Retrieval Augmented Generation (RAG) tasks and applications requiring contextual awareness.
-  
+- It is quantized in a 4-bit version and an 8-bit version suing the prcedure [here](https://github.com/ggerganov/llama.cpp).
+- 
 # Evaluation
 
 We evaluated the model using the same test sets as used for the [Open Ita LLM Leaderboard](https://huggingface.co/spaces/FinancialSupport/open_ita_llm_leaderboard):