Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

Mobile-Agent: The Powerful Mobile Device Operation Assistant Family

InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) excelling in free-form text-image composition and comprehension.

Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought, Instruction-Tuning and Multimodality.

mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding

A family of lightweight multimodal models.

[CVPR2024] The code for "Osprey: Pixel Understanding with Visual Instruction Tuning"

✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models. The first work to correct hallucinations in MLLMs.

Grounded Multimodal Large Language Model with Localized Visual Tokenization

Custom ComfyUI nodes for Vision Language Models, Large Language Models, Image to Music, Text to Music, Consistent and Random Creative Prompt Generation

Personal Project: MPP-Qwen14B & MPP-Qwen-Next(Multimodal Pipeline Parallel based on Qwen-LM). Support [video/image/multi-image] {sft/conversations}. Don't let the poverty limit your imagination! Train your own 8B/14B LLaVA-training-like MLLM on RTX3090/4090 24GB.

Youku-mPLUG: A 10 Million Large-scale Chinese Video-Language Pre-training Dataset and Benchmarks

mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video (ICML 2023)

Awesome_Multimodel is a curated GitHub repository that provides a comprehensive collection of resources for Multimodal Large Language Models (MLLM). It covers datasets, tuning techniques, in-context learning, visual reasoning, foundational models, and more. Stay updated with the latest advancement.

[CVPR2024] Generative Region-Language Pretraining for Open-Ended Object Detection

Cambrian-1 is a family of multimodal LLMs with a vision-centric design.

Official code for Paper "Mantis: Multi-Image Instruction Tuning"

Multimodal chatbot with computer vision capabilities integrated

Official Repo of Graphist

A collection of visual instruction tuning datasets.