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TIGER-Lab
/
EditReward-MiMo-VL-7B-SFT-2508

Image-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
editing
reward
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use TIGER-Lab/EditReward-MiMo-VL-7B-SFT-2508 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use TIGER-Lab/EditReward-MiMo-VL-7B-SFT-2508 with Transformers:

    # Use a pipeline as a high-level helper
    # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
    # You must load the model directly (see below) or downgrade to v4.x with:
    # 'pip install "transformers<5.0.0'
    from transformers import pipeline
    
    pipe = pipeline("image-to-text", model="TIGER-Lab/EditReward-MiMo-VL-7B-SFT-2508")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("TIGER-Lab/EditReward-MiMo-VL-7B-SFT-2508")
    model = AutoModelForMultimodalLM.from_pretrained("TIGER-Lab/EditReward-MiMo-VL-7B-SFT-2508", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
EditReward-MiMo-VL-7B-SFT-2508
16.6 GB
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  • 2 contributors
History: 14 commits
wukeming11's picture
wukeming11
Update README.md
4a702b4 verified 7 months ago
  • .gitattributes
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    initial commit 10 months ago
  • README.md
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  • config.json
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  • model.safetensors
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    xet
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