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  # 🦙 Simple LLaMA Finetuner
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  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lxe/simple-llama-finetuner/blob/master/Simple_LLaMA_FineTuner.ipynb)
 
 
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  Simple LLaMA Finetuner is a beginner-friendly interface designed to facilitate fine-tuning the [LLaMA-7B](https://github.com/facebookresearch/llama) language model using [LoRA](https://arxiv.org/abs/2106.09685) method via the [PEFT library](https://github.com/huggingface/peft) on commodity NVIDIA GPUs. With small dataset and sample lengths of 256, you can even run this on a regular Colab Tesla T4 instance.
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  # 🦙 Simple LLaMA Finetuner
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  [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lxe/simple-llama-finetuner/blob/master/Simple_LLaMA_FineTuner.ipynb)
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+ [![](https://img.shields.io/badge/no-bugs-brightgreen.svg)](https://github.com/lxe/no-bugs)
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+ [![](https://img.shields.io/badge/coverage-%F0%9F%92%AF-green.svg)](https://github.com/lxe/onehundred/tree/master)
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  Simple LLaMA Finetuner is a beginner-friendly interface designed to facilitate fine-tuning the [LLaMA-7B](https://github.com/facebookresearch/llama) language model using [LoRA](https://arxiv.org/abs/2106.09685) method via the [PEFT library](https://github.com/huggingface/peft) on commodity NVIDIA GPUs. With small dataset and sample lengths of 256, you can even run this on a regular Colab Tesla T4 instance.
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