Optimization of models using ShareGPT-4o-Image
To enhance the image generation capability of the open source multimodal model, the following steps can be followed:
- Getting the datasetDownload the 91K high-quality samples included in ShareGPT-4o-Image, containing 45K text-to-image and 46K text-plus-image-to-image samples!
- environmental preparation: Install Python 3.7+ and install the pandas and datasets libraries via pip
- Data loading: Load the dataset directly using the datasets library, code example:
from datasets import load_dataset
dataset = load_dataset("FreedomIntelligence/ShareGPT-4o-Image") - model training: Use the dataset for fine-tuning existing models, focusing on text-image alignment capabilities
- Performance Evaluation: Comparative validation of lifting effect using Janus-4o as a benchmark model
Alternative: if graphics memory is limited, a subset of the dataset can be processed for test training first
This answer comes from the articleShareGPT-4o-Image: an open source multimodal image generation datasetThe
May not be reproduced without permission:AI productivity tools " How to improve image generation for open source multimodal models?
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