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🚀 Introducing ColFlor: An Efficient, OCR-Free Vision-Language Document Retrieval Model 🌟
🚀 Introducing ColFlor: An Efficient, OCR-Free Vision-Language Document Retrieval Model 🌟
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Earlier this year, ColPali revolutionized document retrieval by eliminating the need for error-prone OCR pipelines. Instead, it directly processes the document images. However, with its 3 billion parameters, ColPali is computationally heavy for large-scale applications.
Earlier this year, ColPali revolutionized document retrieval by eliminating the need for error-prone OCR pipelines. Instead, it directly processes the document images. However, with its 3 billion parameters, ColPali is computationally heavy for large-scale applications.
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That’s where ColFlor comes in—a smaller, faster alternative! 🎉 At 17x smaller than ColPali, ColFlor offers a more efficient, OCR-free document retrieval solution, making it ideal for users with limited computing resources (GPU Poor). 💡
That’s where ColFlor comes in—a smaller, faster alternative! 🎉 At 17x smaller than ColPali, ColFlor offers a more efficient, OCR-free document retrieval solution, making it ideal for users with limited computing resources (GPU Poor). 💡
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Key Highlights:
Key Highlights:
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🧠 174M parameters (vs. 3B for ColPali)
🧠 174M parameters (vs. 3B for ColPali)
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⚡ 9.8x faster query encoding, 5.25x faster image encoding
⚡ 9.8x faster query encoding, 5.25x faster image encoding
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📉 Only 1.8% performance drop on text-rich English documents
📉 Only 1.8% performance drop on text-rich English documents
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Check out the full blog post for more insights on modeling, training, and evaluations across various document retrieval tasks! 🚀
Check out the full blog post for more insights on modeling, training, and evaluations across various document retrieval tasks! 🚀
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Also, feel free to try our demo on huggingface 🤗 
Also, feel free to try our demo on huggingface 🤗 
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🔗 Resources:
🔗 Resources:
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📄 Blog post: 
📄 Blog post: 
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https://huggingface.co/blog/ahmed-masry/colflor
https://huggingface.co/blog/ahmed-masry/colflor
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🧠 Model: 
🧠 Model: 
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https://huggingface.co/ahmed-masry/ColFlor
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ahmed-masry/ColFlor
https://huggingface.co/ahmed-masry/ColFlor
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💻 Demo: 
💻 Demo: 
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https://huggingface.co/spaces/ahmed-masry/ColFlor-Demo
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ahmed-masry/ColFlor-Demo
https://huggingface.co/spaces/ahmed-masry/ColFlor-Demo
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🏋️‍♂️ Training code: 
🏋️‍♂️ Training code: 
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https://github.com/AhmedMasryKU/colflor
https://github.com/AhmedMasryKU/colflor
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📊 Evaluation code: 
📊 Evaluation code: 
link
https://github.com/AhmedMasryKU/vidore-benchmark-colflor
https://github.com/AhmedMasryKU/vidore-benchmark-colflor
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🚀 Introducing ColFlor: An Efficient, OCR-Free Vision-Language Document Retrieval Model 🌟

Earlier this year, ColPali revolutionized document retrieval by eliminating the need for error-prone OCR pipelines. Instead, it directly processes the document images. However, with its 3 billion parameters, ColPali is computationally heavy for large-scale applications.

That’s where ColFlor comes in—a smaller, faster alternative! 🎉 At 17x smaller than ColPali, ColFlor offers a more efficient, OCR-free document retrieval solution, making it ideal for users with limited computing resources (GPU Poor). 💡
 
Key Highlights:
🧠 174M parameters (vs. 3B for ColPali)
⚡ 9.8x faster query encoding, 5.25x faster image encoding
📉 Only 1.8% performance drop on text-rich English documents

Check out the full blog post for more insights on modeling, training, and evaluations across various document retrieval tasks! 🚀
Also, feel free to try our demo on huggingface 🤗 

🔗 Resources:
📄 Blog post: https://huggingface.co/blog/ahmed-masry/colflor
🧠 Model: https://huggingface.co/ahmed-masry/ColFlor
💻 Demo: https://huggingface.co/spaces/ahmed-masry/ColFlor-Demo
🏋️‍♂️ Training code: https://github.com/AhmedMasryKU/colflor
📊 Evaluation code: https://github.com/AhmedMasryKU/vidore-benchmark-colflor 

👀
John6666 Chris4K
🔥
adorkin