Instructions to use aomocelin/medsiglip-448-cied-binary-classification-cied-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomocelin/medsiglip-448-cied-binary-classification-cied-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aomocelin/medsiglip-448-cied-binary-classification-cied-detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("aomocelin/medsiglip-448-cied-binary-classification-cied-detection") model = AutoModelForImageClassification.from_pretrained("aomocelin/medsiglip-448-cied-binary-classification-cied-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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