Update README.md

README.md

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 # Model Card for Model ID
 
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+This code fine-tunes Mistral-7B-Instruct 🧠 using the Salesforce/xlam-function-calling-60k dataset to improve its ability to generate accurate structured function calls. It loads the dataset 📂, dynamically removes unnecessary columns like "query" and "answers" for cleaner data, and splits it into 90% training and 10% test for evaluation. The preprocess() function structures data in JSON format 📝, enhancing the model’s reasoning through Chain-of-Thought (CoT) prompting. Special tokens like <tools> and <think> are added to guide structured outputs 🔧. The model is further optimized with bnb_4bit quantization for reduced size (~4.5GB) and improved inference efficiency 🚀. The result is a powerful model that can handle complex API requests with improved accuracy and stability. 🔍
 
 ## Model Details
 This code implements a well-structured process for fine-tuning the Mistral-7B-Instruct model using the Salesforce/xlam-function-calling-60k dataset. The goal is to improve the model’s ability to: