Instructions to use toolevalxm/MedVisionAI-DiagnosticModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/MedVisionAI-DiagnosticModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="toolevalxm/MedVisionAI-DiagnosticModel") 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/MedVisionAI-DiagnosticModel") model = AutoModelForImageClassification.from_pretrained("toolevalxm/MedVisionAI-DiagnosticModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af9e578960298150c870fc336bc2ed6e0d89c1bdba3bd92fcbe81ca537f1eb46
- Size of remote file:
- 35 Bytes
- SHA256:
- b31c6c55e439ffffe157c3332210304a2c7f23a001469615f135ac64b5813f3c
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