Shypd.aiThe largest open index of AI toolsparameter_efficient_instruction_tuning is an Open Source & Models tool that systematically compares parameter-efficient fine-tuning methods for instruction tuning. It uses the NI dataset as a benchmark and provides implementations adapted from existing frameworks.
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parameter_efficient_instruction_tuning is an open-source repository dedicated to the systematic comparison of various parameter-efficient fine-tuning (PEFT) methods for instruction tuning tasks. The project utilizes the SuperNI dataset as its primary benchmark for training and evaluation. Implementations of PEFT methods are adapted from well-known libraries such as adapter-transformers and peft. The repository includes bash scripts for running experiments, optimized for the hfai HPC platform, supporting features like experiment configuration, checkpoint management, and training state validation. It also addresses platform-specific considerations like PyTorch and CUDA compatibility, making it a valuable resource for researchers and developers working on efficient large language model fine-tuning.
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