HenryNdubuaku/super-lazy-autograd
Hand-derived memory-efficient VJPs for tuning LLMs on laptops.
This tool helps machine learning engineers or researchers fine-tune large language models (LLMs) like Qwen or DeepSeek on a personal laptop, even when memory is limited. It takes an existing LLM and a dataset of text, then outputs a specialized version of the model that performs better on your specific tasks. It is designed for those who need to iterate quickly on LLMs without access to high-end data center GPUs.
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Use this if you need to fine-tune a supported large language model for a specific task but only have a laptop with limited memory available.
Not ideal if you have access to powerful GPU servers or cloud computing resources, as dedicated hardware will offer significantly faster and more stable training.
Stars
38
Forks
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Language
Python
License
Apache-2.0
Category
Last pushed
Apr 14, 2025
Commits (30d)
0
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