Instructions to use bumblebee-testing/tiny-random-CLIPModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-CLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="bumblebee-testing/tiny-random-CLIPModel") 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("bumblebee-testing/tiny-random-CLIPModel") model = AutoModelForZeroShotImageClassification.from_pretrained("bumblebee-testing/tiny-random-CLIPModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b093513ac1559c3d975b4bafa607f027d17f5c563eb1107725f05e79fae91535
- Size of remote file:
- 535 kB
- SHA256:
- 0be7dd0328f6211c7e8fae59157788010b4b266c45cfb69fff569841dc5b4724
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