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
Why the performence between Api and transformers is so different?
#26
by BarkRobot - opened
How can I get the same performance like Api in local transformer code.
This also confuses me. I guess the difference is caused by the data processing(normalization)