Instructions to use yujiepan/clip-vit-tiny-random-patch14-336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yujiepan/clip-vit-tiny-random-patch14-336 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="yujiepan/clip-vit-tiny-random-patch14-336") 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("yujiepan/clip-vit-tiny-random-patch14-336") model = AutoModelForZeroShotImageClassification.from_pretrained("yujiepan/clip-vit-tiny-random-patch14-336") - Notebooks
- Google Colab
- Kaggle