Last updated 03-26-2024
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Stanford's Alpaca
Stanford Alpaca is a repository on GitHub developed by tatsu-lab that provides code and documentation for training Alpaca models, based on Stanford's LLaMA, and for generating data. The Alpaca model is an instruction-following AI model fine-tuned on a subset of the LLaMA dataset for specific applications. The primary aim of the project is to contribute to the research community by providing resources that can assist in building instruction-based models. Users can find the dataset, data generation process, and the fine-tuning code within the repository. It's important to note that the Alpaca model is intended for research purposes only, and the associated dataset is licensed for non-commercial use under CC BY NC 4.0. The repository encourages collaborative development, while also highlighting its limitations, urging researchers to use it with caution and contribute to its ethical development.
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Dataset Access: Access to the 52K data used for fine-tuning the model.
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Data Generation Code: Code for generating the necessary data for training.
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Fine-Tuning Procedure: Detailed instructions and procedures for fine-tuning the Alpaca models.
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Model Weights Recovery: Mechanism for recovering Alpaca-7B weights from the released weight difference.
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Licensing Information: Clear license indications for code and data usage.
1) What is Stanford Alpaca?
tanford Alpaca is a project aimed at developing and distributing an instruction-following LLaMA model for research purposes.
2) What does the Stanford Alpaca repository contain?
he repository includes a dataset, data generation code, fine-tuning procedures, and a weight difference file for the Alpaca-7B model.
3) Does Stanford Alpaca include code for training the model?
es, the repo provides code for both generating the data and the fine-tuning process.
4) What are the usage restrictions for Stanford Alpaca?
tanford Alpaca is licensed for non-commercial, research-only use under CC BY NC 4.
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5) Are the model weights of the Alpaca-7B model released?
s of the knowledge cutoff date, intention to release has been expressed, pending permissions from the creators of LLaMA.
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