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# **Blazer.1-7B-Vision**
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Blazer.1-7B-Vision `4-bit precision` is based on the Qwen2-VL model, fine-tuned for raw document annotation extraction, optical character recognition (OCR), and solving math problems with LaTeX formatting. This model integrates a conversational approach with advanced visual and textual understanding to effectively handle multi-modal tasks. Key enhancements include state-of-the-art (SoTA) performance in understanding images of various resolutions and aspect ratios, as demonstrated by its success on visual
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# **Use it With Transformer**
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# **Blazer.1-7B-Vision**
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Blazer.1-7B-Vision `4-bit precision` is based on the Qwen2-VL model, fine-tuned for raw document annotation extraction, optical character recognition (OCR), and solving math problems with LaTeX formatting. This model integrates a conversational approach with advanced visual and textual understanding to effectively handle multi-modal tasks. Key enhancements include state-of-the-art (SoTA) performance in understanding images of various resolutions and aspect ratios, as demonstrated by its success on visual
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understanding benchmarks such as MathVista, DocVQA, RealWorldQA, and MTVQA. Additionally, it excels in video comprehension, capable of processing videos over 20 minutes in length for high-quality video-based question answering, dialogue, and content creation. Blazer.1-7B-Vision also functions as an intelligent agent capable of operating devices like mobile phones and robots, thanks to its complex reasoning and decision-making abilities, enabling automatic operations based on visual environments and text instructions. To serve global users, the model offers multilingual support, understanding texts in a wide range of languages, including English, Chinese, most European languages, Japanese, Korean, Arabic, and Vietnamese.
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# **Use it With Transformer**
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