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  **Code-Jamba-v0.1**
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  This model is trained upon my dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT) and [Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback). It is finetuned on Jamba-v0.1 .
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- This model is very very good in Code generation is various languages such as Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell, etc..
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  This model will also generate detailed explanation/logic behind each code.
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  This model uses ChatML prompt format.
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  **Training**
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- Entire dataset was trained on 2 x H100 94GB. For 3 epoch, training took 162 hours. Axolotl along with DeepSpeed codebase was used for training purpose. This was trained on Jamba-v0.1 by AI21Labs.
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  This is a qlora model. Links for quantized models will be updated very soon.
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  **Code-Jamba-v0.1**
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  This model is trained upon my dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT) and [Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback). It is finetuned on Jamba-v0.1 .
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+ It is very very good in Code generation in various languages such as **Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell**, etc..
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  This model will also generate detailed explanation/logic behind each code.
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  This model uses ChatML prompt format.
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  **Training**
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+ Entire dataset was trained on **2 x H100** 94GB. For 3 epoch, training took **162 hours**. Axolotl along with DeepSpeed codebase was used for training purpose. This was trained on Jamba-v0.1 by AI21Labs.
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  This is a qlora model. Links for quantized models will be updated very soon.
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