Zero-Shot Image Classification
Transformers
PyTorch
Safetensors
English
clip
vision
language
fashion
ecommerce
Instructions to use risedev/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use risedev/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="risedev/test") 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("risedev/test") model = AutoModelForZeroShotImageClassification.from_pretrained("risedev/test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d62c7ab1435ead1d22f07ce63266f690780a67a7d278fad7ce84a03e678ab5ee
- Size of remote file:
- 605 MB
- SHA256:
- 4977e3a54929eccf065ce449aeaf296f0e5cb6b28e8798c3c97d67cb2f6dafc9
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