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  - multimodal
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  library_name: transformers
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Qwen2.5-VL-32B-Instruct
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- <a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
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- <img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
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- </a>
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-
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  ## Latest Updates:
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  In addition to the original formula, we have further enhanced Qwen2.5-VL-32B's mathematical and problem-solving abilities through reinforcement learning. This has also significantly improved the model's subjective user experience, with response styles adjusted to better align with human preferences. Particularly for objective queries such as mathematics, logical reasoning, and knowledge-based Q&A, the level of detail in responses and the clarity of formatting have been noticeably enhanced.
 
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  - multimodal
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  library_name: transformers
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  ---
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+ <div>
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+ <p style="margin-bottom: 0; margin-top: 0;">
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+ <strong>See <a href="https://huggingface.co/collections/unsloth/qwen25-vl-all-versions-679ca6c784fad5bd976a05a1">our collection</a> for versions of Qwen2.5-VL including 4-bit & dynamic formats.</strong>
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+ </p>
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+ <div style="display: flex; gap: 5px; align-items: center; ">
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+ <a href="https://github.com/unslothai/unsloth/">
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+ <img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
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+ </a>
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+ <a href="https://discord.gg/unsloth">
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+ <img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
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+ </a>
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+ <a href="https://docs.unsloth.ai/">
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+ <img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
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+ </a>
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+ </div>
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+ </div>
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  # Qwen2.5-VL-32B-Instruct
 
 
 
 
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  ## Latest Updates:
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  In addition to the original formula, we have further enhanced Qwen2.5-VL-32B's mathematical and problem-solving abilities through reinforcement learning. This has also significantly improved the model's subjective user experience, with response styles adjusted to better align with human preferences. Particularly for objective queries such as mathematics, logical reasoning, and knowledge-based Q&A, the level of detail in responses and the clarity of formatting have been noticeably enhanced.