Instructions to use openai/clip-vit-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/clip-vit-large-patch14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-large-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("openai/clip-vit-large-patch14") model = AutoModelForZeroShotImageClassification.from_pretrained("openai/clip-vit-large-patch14") - Notebooks
- Google Colab
- Kaggle
Interesting work β mobile AI perspective
#55
by 3morixd - opened
We're always scanning HuggingFace for models that could work on mobile.
At Dispatch AI (FZE, UAE), we benchmark on 40 phones (Snapdragon 865). If this model fits mobile criteria, we'll quantize and test it.
Open weights move everything forward. Thanks for the release.
- Dispatch AI (FZE), Sharjah UAE