Instructions to use FLIP-dataset/FLIP-large-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FLIP-dataset/FLIP-large-14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="FLIP-dataset/FLIP-large-14") 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("FLIP-dataset/FLIP-large-14") model = AutoModelForZeroShotImageClassification.from_pretrained("FLIP-dataset/FLIP-large-14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9eb1f111518821e30a4095b971e87f521f13a5204a5279500a79901b1efd643
- Size of remote file:
- 1.71 GB
- SHA256:
- 56e702922cfea759a44bf8062415a1380b0e0f03afe1be3691f67f32467fe273
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