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xingxm
/
HiVG-3B-Base

Image-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
svg
hivg
vector-graphics
text-to-svg
image-to-svg
hierarchical-tokenization
autoregressive-generation
code-generation
text-generation-inference
Model card Files Files and versions
xet
Community
1

Instructions to use xingxm/HiVG-3B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use xingxm/HiVG-3B-Base 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="xingxm/HiVG-3B-Base")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForImageTextToText
    
    processor = AutoProcessor.from_pretrained("xingxm/HiVG-3B-Base")
    model = AutoModelForImageTextToText.from_pretrained("xingxm/HiVG-3B-Base")
  • Notebooks
  • Google Colab
  • Kaggle
HiVG-3B-Base
8.16 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
xingxm's picture
xingxm
Update README.md
259cba9 verified 25 days ago
  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • chat_template.jinja
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  • config.json
    3.33 kB
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  • generation_config.json
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  • merges.txt
    1.67 MB
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  • model-00001-of-00002.safetensors
    4.96 GB
    xet
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  • model-00002-of-00002.safetensors
    3.18 GB
    xet
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  • model.safetensors.index.json
    65.5 kB
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  • preprocessor_config.json
    829 Bytes
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    11.7 MB
    xet
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  • tokenizer_config.json
    229 kB
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  • video_preprocessor_config.json
    913 Bytes
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  • vocab.json
    2.78 MB
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