Minimal LLM Post-Training Experiments on an 8GB GPU (SFT, DPO, GRPO)
Minimal, readable LLM post-training experiments on one 8GB GPU. Measures forgetting, seed variance, and RL emergence. - pochenai/nano-llm-posttraining
Minimal LLM Post-Training Experiments on an 8GB GPU (SFT, DPO, GRPO) launched on August 1, 2026 with 21 votes, #737 of 23,274 launches that month and more than 90% of that year's launches.
In plain words
This project provides code and guidance for fine-tuning large language models using supervised fine-tuning (SFT), direct preference optimization (DPO), and GRPO techniques on consumer-grade hardware with 8GB of GPU memory. It is designed for researchers and developers who want to experiment with model post-training methods without access to expensive computing infrastructure. The work demonstrates practical approaches to training alignment techniques on resource-constrained systems.
written from the facts on this page · September 2026
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