Instructions to use nmitchko/ML1-previews with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nmitchko/ML1-previews with PEFT:
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- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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`nmitchko/ML1-34b-previews` is a large language model repository of LoRA checkpoints specifically fine-tuned to add text-book synthesized data in the style of Phi 1/1.5.
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It is based on [`codellama-34b-hf`](https://huggingface.co/codellama/CodeLlama-34b-hf) at 34 billion parameters.
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The primary goal of this model is to
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It was trained using [LoRA](https://arxiv.org/abs/2106.09685), specifically [QLora Multi GPU](https://github.com/ChrisHayduk/qlora-multi-gpu), to reduce memory footprint.
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See Training Parameters for more info This Lora supports 4-bit and 8-bit modes.
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`nmitchko/ML1-34b-previews` is a large language model repository of LoRA checkpoints specifically fine-tuned to add text-book synthesized data in the style of Phi 1/1.5.
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It is based on [`codellama-34b-hf`](https://huggingface.co/codellama/CodeLlama-34b-hf) at 34 billion parameters.
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The primary goal of this model is to test various fine tuning methods around high quality data.
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It was trained using [LoRA](https://arxiv.org/abs/2106.09685), specifically [QLora Multi GPU](https://github.com/ChrisHayduk/qlora-multi-gpu), to reduce memory footprint.
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See Training Parameters for more info This Lora supports 4-bit and 8-bit modes.
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