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Ngit
/
clip-rsicd

Zero-Shot Image Classification
Transformers
PyTorch
JAX
clip
Model card Files Files and versions
xet
Community
1

Instructions to use Ngit/clip-rsicd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Ngit/clip-rsicd with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="Ngit/clip-rsicd")
    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("Ngit/clip-rsicd")
    model = AutoModelForZeroShotImageClassification.from_pretrained("Ngit/clip-rsicd")
  • Notebooks
  • Google Colab
  • Kaggle
clip-rsicd
1.21 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Ngit's picture
Ngit
commit
631c7a8 almost 4 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • config.json
    4.13 kB
    commit almost 4 years ago
  • flax_model.msgpack
    605 MB
    xet
    commit almost 4 years ago
  • merges.txt
    525 kB
    commit almost 4 years ago
  • preprocessor_config.json
    316 Bytes
    commit almost 4 years ago
  • pytorch_model.bin
    605 MB
    xet
    commit almost 4 years ago
  • special_tokens_map.json
    389 Bytes
    commit almost 4 years ago
  • tokenizer.json
    2.22 MB
    commit almost 4 years ago
  • tokenizer_config.json
    568 Bytes
    commit almost 4 years ago
  • vocab.json
    862 kB
    commit almost 4 years ago