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README.md

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 With MiniCPM-Visual-Embedding, it is possible to directly build knowledge base with raw PDF/Book/Document without any OCR technique nor OCR pipeline. The model only takes images as document-side inputs and produce vectors representing document pages. minicpm-visual-embedding-v0 is trained with over 30k paired query - visual document pages, including textual document, visual document, arxiv figures, industry documents, textbooks, ebooks, etc. The performance of minicpm-visual-embedding-v0 is on a par with a text embedding on text-oriented documents, and an advantages on visually-intensive documents.
 
-[Github Repo](https://github.com/bokesyo/minicpm-visual-embedding)
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 ![Memex Archtechture](images/memex.png)
 
 # News
 
 - 2024-06-27: We released our first visual embedding model checkpoint minicpm-visual-embedding-v0 on [huggingface](https://huggingface.co/RhapsodyAI/minicpm-visual-embedding-v0).
 
-- 2024-05-08: We [committed](https://github.com/bokesyo/minicpm-visual-embedding) our training code (full-parameter tuning with GradCache and DeepSpeed, supports large batch size across multiple GPUs with zero-stage1) and eval code. 
+- 2024-05-08: We [open-sourced](https://github.com/bokesyo/minicpm-visual-embedding) our training code (full-parameter tuning with GradCache and DeepSpeed, supports large batch size across multiple GPUs with zero-stage1) and eval code. 
 
 # Get started