Summarization
Transformers
TensorFlow
English
clip
zero-shot-image-classification
Eval Results (legacy)
Instructions to use ydshieh/clip-vit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/clip-vit-base-patch32 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="ydshieh/clip-vit-base-patch32")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("ydshieh/clip-vit-base-patch32") model = AutoModelForZeroShotImageClassification.from_pretrained("ydshieh/clip-vit-base-patch32") - Notebooks
- Google Colab
- Kaggle