shinning the spotlight on CogVLM

• llama.cpp

  788 58,856 10.0 C++

  LLM inference in C/C++

I was casually sifting through the llama.cpp discussions when i found a particularly interesting conversation.

• CogVLM

  16 5,355 9.0 Python

  a state-of-the-art-level open visual language model | 多模态预训练模型

  

A core Llama.cpp contributor, named cmp-nct, discovered stumbled upon what might be the next leap forward for vision/language models. CogVLM (which uses a Vicuna 7B language model combined with a 9B vision tower) excels particularly in OCR (Optical Character Recognition), detail detection, and minimal hallucinations. It effectively understands both handwritten and typed text, context, fine details, and background graphics. It even provides pixel coordinates for small visual targets. CovVLM surpasses other models like llava-1.5 and Qwen-VL in performance.

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• Woodpecker

  2 561 8.9 Python

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

Woodpecker: Hallucination Correction for Multimodal Large Language Models https://github.com/BradyFU/Woodpecker

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