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qihoo360
/
fg-clip2-base

Zero-Shot Image Classification
Transformers
Safetensors
English
Chinese
fgclip2
text-generation
clip
custom_code
Model card Files Files and versions
xet
Community
2

Instructions to use qihoo360/fg-clip2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use qihoo360/fg-clip2-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="qihoo360/fg-clip2-base", trust_remote_code=True)
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("qihoo360/fg-clip2-base", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
fg-clip2-base
1.58 GB
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  • 3 contributors
History: 17 commits
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xiechunyu
Update README.md
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  • FGCLIP2_compare_all_n.png
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  • FGCLIP2_dfcolor_cat_all_2K.png
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  • README.md
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  • config.json
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  • configuration_fgclip2.py
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  • model.safetensors
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  • modeling_fgclip2.py
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  • preprocessor_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer.model
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  • tokenizer_config.json
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