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  license: cc-by-nc-nd-4.0
 
 
 
 
 
 
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  license: cc-by-nc-nd-4.0
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+ datasets:
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+ - ajibawa-2023/Code-74k-ShareGPT
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+ language:
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+ - en
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+ tags:
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+ - code
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  ---
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+
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+ **Code-33B**
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+
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+ Large Language Models (LLMs) are good with code generations. Sometimes they do make mistakes in code generation. How about if they can give detailed explanation along with the code.
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+ This is what I have tried over here. The base Llama-1 model was used for training purpose. It is trained on around 74000 set of codes. Each set having 2 conversations.
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+ Along with Python, Java, JavaScript, GO, C++, Rust etc. code with detailed explanation is used for training purpose. It is built upon using my existing Dataset [Python-Code-23k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Python-Code-23k-ShareGPT).
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+ This conversation is in Vicuna/ShareGPT format. Each set, along with code, has detailed explanation.
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+
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+ I have released the new data [Code-74k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-74k-ShareGPT) on which this Model is trained.
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+ **Training:**
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+ Entire dataset was trained on Azure 4 x A100 80GB. For 3 epoch, training took 6 days & 5 hours. DeepSpeed codebase was used for training purpose. This was trained on Llama-2 by Meta.
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+
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+ This is a full fine tuned model. Links for quantized models will be updated soon.
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+
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+ **GPTQ GGUF & AWQ**
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+
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+ GPTQ: TBA
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+
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+ GGUF: TBA
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+ AWQ: TBA
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+ **Example Prompt:**
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+ ```
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+ This is a conversation with your helpful AI assistant. AI assistant can generate Code in various Programming Languages along with necessary explanation.
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+
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+ Context
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+ You are a helpful AI assistant.
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+
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+ USER: <prompt>
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+ ASSISTANT:
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+ ```
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+
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+ You can modify above Prompt as per your requirement. I have used ShareGPT/Vicuna format v1.1 .
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+ I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
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+ Thank you for your love & support.