Instructions to use V4ldeLund/clip-vit-base-patch16-da-lora-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use V4ldeLund/clip-vit-base-patch16-da-lora-text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="V4ldeLund/clip-vit-base-patch16-da-lora-text") 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("V4ldeLund/clip-vit-base-patch16-da-lora-text") model = AutoModelForZeroShotImageClassification.from_pretrained("V4ldeLund/clip-vit-base-patch16-da-lora-text") - Notebooks
- Google Colab
- Kaggle