Instructions to use toolevalxm/MedicalVisionModel-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/MedicalVisionModel-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="toolevalxm/MedicalVisionModel-TestRepo") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("toolevalxm/MedicalVisionModel-TestRepo") model = AutoModelForImageClassification.from_pretrained("toolevalxm/MedicalVisionModel-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c59c27a4cba7d157be6e5068627b382189bdddcc74a9242daa01335f2bdbe354
- Size of remote file:
- 27 Bytes
- SHA256:
- 0cae944217dbb27578f0ceaacd85f463aaddaa6b2726c28de5c57f2748a748df
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