[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的开源多模态对话模型
The official repo of Qwen-VL (通义千问-VL) chat & pretrained large vision language model proposed by Alibaba Cloud.
DeepSeek-VL: Towards Real-World Vision-Language Understanding
Align Anything: Training All-modality Model with Feedback
🚀 「大模型」1小时从0训练26M参数的视觉多模态VLM！🌏 Train a 26M-parameter VLM from scratch in just 1 hours!
Official repo for "Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models"
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
Collection of AWESOME vision-language models for vision tasks
The official repo of MiniMax-Text-01 and MiniMax-VL-01, large-language-model & vision-language-model based on Linear Attention
The Cradle framework is a first attempt at General Computer Control (GCC). Cradle supports agents to ace any computer task by enabling strong reasoning abilities, self-improvment, and skill curation, in a standardized general environment with minimal requirements.
The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
A collection of original, innovative ideas and algorithms towards Advanced Literate Machinery. This project is maintained by the OCR Team in the Language Technology Lab, Tongyi Lab, Alibaba Group.
The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
Get clean data from tricky documents, powered by vision-language models ⚡
[CVPR 2025] Open-source, End-to-end, Vision-Language-Action model for GUI Agent & Computer Use.
日本語LLMまとめ - Overview of Japanese LLMs
This series will take you on a journey from the fundamentals of NLP and Computer Vision to the cutting edge of Vision-Language Models.
Implementation for Describe Anything: Detailed Localized Image and Video Captioning
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