Instructions to use OFA-Sys/chinese-clip-vit-huge-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OFA-Sys/chinese-clip-vit-huge-patch14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="OFA-Sys/chinese-clip-vit-huge-patch14") 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("OFA-Sys/chinese-clip-vit-huge-patch14") model = AutoModelForZeroShotImageClassification.from_pretrained("OFA-Sys/chinese-clip-vit-huge-patch14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35f0ee6d0361b4bc4f88a667cc6eb9e73edfd1fad8947b8ab29a0fd6c9f5b074
- Size of remote file:
- 3.83 GB
- SHA256:
- d3bc35de533b12cc69ce6c0604a6737c21eb2b84068384a0805d4f32c90dbfdb
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