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README.md
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@@ -9,8 +9,8 @@ Making evaluating and fine-tuning LLaMA models with low-rank adaptation (LoRA) e
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* [1-click up and running in Google Colab](https://colab.research.google.com/github/zetavg/LLaMA-LoRA/blob/main/LLaMA_LoRA.ipynb).
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* Loads and stores data in Google Drive.
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* Evaluate various LLaMA LoRA models stored in your folder or from Hugging Face.<br /><a href="https://
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* Fine-tune LLaMA models with different prompt templates and training dataset format.<br /><a href="https://
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* Load JSON and JSONL datasets from your folder, or even paste plain text directly into the UI.
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* Supports Stanford Alpaca [seed_tasks](https://github.com/tatsu-lab/stanford_alpaca/blob/main/seed_tasks.jsonl), [alpaca_data](https://github.com/tatsu-lab/stanford_alpaca/blob/main/alpaca_data.json) and [OpenAI "prompt"-"completion"](https://platform.openai.com/docs/guides/fine-tuning/data-formatting) format.
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* [1-click up and running in Google Colab](https://colab.research.google.com/github/zetavg/LLaMA-LoRA/blob/main/LLaMA_LoRA.ipynb).
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* Loads and stores data in Google Drive.
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* Evaluate various LLaMA LoRA models stored in your folder or from Hugging Face.<br /><a href="https://youtu.be/A3kb4VkDWyY"><img width="640px" src="https://user-images.githubusercontent.com/3784687/230272844-09f7a35b-46bf-4101-b15d-4ddf243b8bef.gif" /></a>
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* Fine-tune LLaMA models with different prompt templates and training dataset format.<br /><a href="https://youtu.be/5Db9U8PsaUk"><img width="640px" src="https://user-images.githubusercontent.com/3784687/230277315-9a91d983-1690-4594-9d54-912eda8963ee.gif" /></a>
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* Load JSON and JSONL datasets from your folder, or even paste plain text directly into the UI.
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* Supports Stanford Alpaca [seed_tasks](https://github.com/tatsu-lab/stanford_alpaca/blob/main/seed_tasks.jsonl), [alpaca_data](https://github.com/tatsu-lab/stanford_alpaca/blob/main/alpaca_data.json) and [OpenAI "prompt"-"completion"](https://platform.openai.com/docs/guides/fine-tuning/data-formatting) format.
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