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Coobiw/README.md

Hi ! Here is Coobiw πŸ‘‹

πŸ™‹β€β™‚οΈ About Me:

  • πŸ‘¨β€πŸ¦° I’m currently a Master of Science candidate of Peking University (PKU).
  • πŸ‘¦ Before that, I received the Honours Bachelor, Huazhong University of Science and Technology (HUST).
  • ❀️‍πŸ”₯ Now, I am intersted in Multi-modal Learning especially MLLM.

πŸ˜‹ Projects:

  • πŸ’₯ In 2023 summer, I take part in OSPP(Open Source Promotion Plan) Summer Camp , with the honor of contributing for MMPretrain to build prompt-based classifier.
    • Now, the implement of zero-shot CLIP classifier has been merged to the main branch. PR Link
    • The implement of RAM(Recognize Anything Model) has been merged to the dev branch. Welcome to use the gradio WebUI to test it on MMPretrain! PR Link
  • πŸ’₯ 2023.11-2024.5: MPP-Qwen-Next is released! All training is conducted on 3090/4090 GPUs. To prevent poverty (24GB of VRAM) from limiting imagination, I implemented an MLLM version based on deepspeed Pipeline Parallel. The Repo supports {video/image/multi-image} {single/multi-turn} conversations. Let's have a try! MPP-Qwen-Next.
  • πŸ’₯ 2024.9: We release ChartMoE, a multimodal large language model with Mixture-of-Expert connector, for advanced chart 1)understanding, 2)replot, 3)editing, 4)highlighting and 5)transformation. arXiv Project Page Codebase


Anurag's GitHub stats

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  1. MPP-LLaVA MPP-LLaVA Public

    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! Tr…

    Jupyter Notebook 350 19

  2. IDEA-FinAI/ChartMoE IDEA-FinAI/ChartMoE Public

    Python 9

  3. open-mmlab/mmpretrain open-mmlab/mmpretrain Public

    OpenMMLab Pre-training Toolbox and Benchmark

    Python 3.4k 1.1k

  4. IP-IQA IP-IQA Public

    [ICME2024, Official Code] for paper "Bringing Textual Prompt to AI-Generated Image Quality Assessment"

    Python 12

  5. TriVQA TriVQA Public

    [CVPRW2024, Official Code] for paper "Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text Consistency and Domain Distribution Gap".

    10