Shypd.aiThe largest open index of AI toolsLLaMA-Adapter is an open-source tool for fine-tuning LLaMA models efficiently. It enables instruction-following capabilities within one hour using only 1.2M parameters.
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LLaMA-Adapter is an open-source toolkit designed for the efficient fine-tuning of LLaMA models, allowing them to follow instructions with minimal computational resources. This method introduces only 1.2 million learnable parameters, enabling the transformation of a LLaMA model into an instruction-following model within approximately one hour. It utilizes a novel Zero-init Attention mechanism with a zero gating mechanism to stabilize training and adaptively incorporate instructional signals. The tool supports both instruction-following and multi-modal LLaMA models, including LLaMA-Adapter V1, V2, and ImageBind-LLM. It also offers integration with LangChain and provides code for reproducing Gorilla models.
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