Instructions to use 0914eagle/Clip_ViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0914eagle/Clip_ViT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="0914eagle/Clip_ViT") 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("0914eagle/Clip_ViT") model = AutoModelForZeroShotImageClassification.from_pretrained("0914eagle/Clip_ViT") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoProcessor, AutoModelForZeroShotImageClassification
processor = AutoProcessor.from_pretrained("0914eagle/Clip_ViT")
model = AutoModelForZeroShotImageClassification.from_pretrained("0914eagle/Clip_ViT")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="0914eagle/Clip_ViT") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )