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Azazelle
/
LongClip-L-diffusers

Zero-Shot Image Classification
Transformers
PyTorch
clip
Model card Files Files and versions
xet
Community
2

Instructions to use Azazelle/LongClip-L-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Azazelle/LongClip-L-diffusers with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="Azazelle/LongClip-L-diffusers")
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoProcessor, AutoModelForZeroShotImageClassification
    
    processor = AutoProcessor.from_pretrained("Azazelle/LongClip-L-diffusers")
    model = AutoModelForZeroShotImageClassification.from_pretrained("Azazelle/LongClip-L-diffusers")
  • Notebooks
  • Google Colab
  • Kaggle
LongClip-L-diffusers
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  • 1 contributor
History: 5 commits
Azazelle's picture
Azazelle
Upload preprocessor_config.json
3fa04e3 verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • config.json
    4.52 kB
    Upload 2 files about 2 years ago
  • merges.txt
    525 kB
    Upload 5 files about 2 years ago
  • preprocessor_config.json
    316 Bytes
    Upload 5 files about 2 years ago
  • pytorch_model.bin
    1.71 GB
    xet
    Rename longclip-L.pt to pytorch_model.bin about 2 years ago
  • special_tokens_map.json
    389 Bytes
    Upload 5 files about 2 years ago
  • tokenizer_config.json
    905 Bytes
    Upload 5 files about 2 years ago
  • vocab.json
    961 kB
    Upload 5 files about 2 years ago