NiuTrans/Vision-LLM-Alignment
This repository contains the code for SFT, RLHF, and DPO, designed for vision-based LLMs, including the LLaVA models and the LLaMA-3.2-vision models.
This project helps machine learning researchers and engineers refine vision-based large language models (Vision-LLMs). It takes a pre-trained Vision-LLM (like LLaVA or LLaMA-3.2-Vision) and human preference data as input to improve the model's ability to follow instructions and generate helpful, trustworthy responses based on images and text. The output is an 'aligned' Vision-LLM that performs better on real-world visual-language tasks.
118 stars. No commits in the last 6 months.
Use this if you need to fine-tune existing Vision-LLMs to better align with human preferences for safety, helpfulness, and instruction-following, especially for multi-image prompts.
Not ideal if you are looking for a pre-trained, ready-to-use Vision-LLM or if your primary focus is on training a Vision-LLM from scratch without alignment.
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118
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10
Language
Python
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Last pushed
Jun 18, 2025
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