streamline the fine-tuning process for multimodal models: PaliGemma 2, Florence-2, and Qwen2.5-VL

MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.

Testing and evaluating the capabilities of Vision-Language models (PaliGemma) in performing computer vision tasks such as object detection and segmentation.

使用LLaMA-Factory微调多模态大语言模型的示例代码 Demo of Finetuning Multimodal LLM with LLaMA-Factory

Use PaliGemma to auto-label data for use in training fine-tuned vision models.

Minimalist implementation of PaliGemma 2 & PaliGemma VLM from scratch

PyTorch implementation of PaliGemma 2

Notes for the Vision Language Model implementation by Umar Jamil

AI-powered tool to convert text from images into your desired language. Gemma vision model and multilingual model are used.

A Python, Shell project focusing on Training Process, License, Author, 1. Defect Detection, PaliGemma Multitask.

Leverage PaliGemma 2's DOCCI fine-tuned variant capabilities using LitServe.

Image Captioning with PaliGemma 2 Vision Language Model.

Leverage PaliGemma 2 mix model variant capabilities using LitServe.

MAESTRO is an AI-powered research application designed to streamline complex research tasks.