Instructions to use apple/DFN-public with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/DFN-public with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="apple/DFN-public") 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("apple/DFN-public") model = AutoModelForZeroShotImageClassification.from_pretrained("apple/DFN-public") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cffeadebac7c536ef6e338374940bbbabfacad521078a42127c24cef89c5bb6c
- Size of remote file:
- 605 MB
- SHA256:
- 0d2f82e2fb2fd0ff068582a1d29c8cd92ec9a8621b822dba792795016259e661
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