Instructions to use toolevalxm/MedVisionNet-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/MedVisionNet-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="toolevalxm/MedVisionNet-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/MedVisionNet-TestRepo") model = AutoModelForImageClassification.from_pretrained("toolevalxm/MedVisionNet-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e267388b65bf198f92b920958972c1248e41266b74aaecd3bbb44090146463a0
- Size of remote file:
- 23 Bytes
- SHA256:
- 6a6b3fc68156d2a235c5a1d74f97760e50ce342aa7808c84a7a92b9920df0667
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