Instructions to use openai/clip-vit-large-patch14-336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/clip-vit-large-patch14-336 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-patch14-336") 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("openai/clip-vit-large-patch14-336") model = AutoModelForZeroShotImageClassification.from_pretrained("openai/clip-vit-large-patch14-336") - Notebooks
- Google Colab
- Kaggle
Update `preprocessor_config.json` to use `image_processor_type` instead of `feature_extractor_type`.
#11
by TerryPan0525 - opened
Could not find image processor class in the image processor config or the model config. Loading based on pattern matching with the model's feature extractor configuration. Please open a PR/issue to update preprocessor_config.json to use image_processor_type instead of feature_extractor_type. This warning will be removed in v4.40.