Yuliang-Liu/Monkey

Health v2 · maintenance only

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1951 stars · 140 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Monkey is a large multi-modal model (LMM) research project from CVPR 2024 that improves image understanding via higher input resolution and detailed text labels, with variants like TextMonkey for OCR-free document understanding. It provides training code, model weights, and caption datasets for multimodal vision-language research.

Use cases

• run a multimodal LLM for image captioning
• understand documents without OCR pipelines
• generate detailed image descriptions
• fine-tune a vision-language model on high-resolution images
• benchmark multimodal models on OCR and VQA tasks

When to choose

• you need an open multimodal model with strong OCR-free document understanding
• you want research code and pretrained weights for high-resolution image understanding

When to avoid

• you need a production-ready hosted vision API
• you lack GPU resources for large model inference

Facets

library · maturity active

machine-learning deep-learning llm-inference ocr image-processing nlp artificial-intelligence large-language-models computer-vision image-processing python multimodal vision-language-model ocr-free cvpr-2024 model-weights research natural-language-processing gpu linux

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