Update README.md

README.md

@@ -1,3 +1,40 @@
 ---
 license: cc-by-nc-nd-4.0
+datasets:
+- ajibawa-2023/Python-Code-23k-ShareGPT
+language:
+- en
+tags:
+- code
 ---
+
+**Python-Code-33B**
+
+Large Language Models (LLMs) are good with code generations. Sometimes LLMs do make mistakes in code generation. How about if they can give detailed explanation along with the code.
+This is what I have tried over here. The base Llama-2 model was used for training purpose. It is trained on around 23000+ set of codes. Each set having 2 conversations.
+This data was generated using GPT-3.5, GPT-4 etc. This conversation is in Vicuna/ShareGPT format. Each set, along with code, has detailed explanation. 
+I have released the [data](https://huggingface.co/datasets/ajibawa-2023/Python-Code-23k-ShareGPT).
+
+**Training:**
+Entire dataset was trained on Azure 4 x A100 80GB. For 3 epoch, training took 42 hours. DeepSpeed codebase was used for training purpose. This was trained on Llama-2 by Meta.
+
+
+**GPTQ GGML & AWQ**
+
+GPTQ: TBA
+
+GGUF: TBA
+
+AWQ: TBA
+
+
+**Example Prompt:**
+```
+This is a conversation with your helpful AI assistant. AI assistant can generate Python Code along with necessary explanation.
+
+Context
+You are a helpful AI assistant.
+
+USER: <prompt>
+ASSISTANT:
+```