Update README.md

README.md

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 This model focuses on fine-tuning the Llama-2 7B large language model for Python code generation. The project leverages Ludwig, an open-source toolkit, and a dataset of 500k Python code samples from Hugging Face. The model applies techniques such as prompt templating, zero-shot inference, and few-shot learning, enhancing the model's performance in generating Python code snippets efficiently.
 
 - **Developed by:** Kevin Geejo, Aniket Yadav, Rishab Pandey  
-- **Funded by [optional]:** No specific funding agency identified  
-- **Shared by [optional]:** No additional sharing information provided  
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 - **Model type:** Fine-tuned Llama-2 7B for Python code generation  
 - **Language(s) (NLP):** Python (for code generation tasks)  
 - **License:** Not explicitly mentioned, but Llama-2 models are typically governed by Meta AI’s open-source licensing  
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 <!-- Provide the basic links for the model. -->
 
-- **Repository:** Hugging Face (trained models uploaded, no specific link provided)  
-- **Paper [optional]:** Not explicitly mentioned  
-- **Demo [optional]:** No demo link provided  
+- **Repository:** Hugging Face
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 ## Uses
 
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 Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute).  
 
-- **Hardware Type:** Not specified  
-- **Hours used:** Not specified  
-- **Cloud Provider:** Not specified  
-- **Compute Region:** Not specified  
-- **Carbon Emitted:** Not specified  
 
-## Technical Specifications [optional]
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 ### Model Architecture and Objective