Instructions to use toolevalxm/RadiologyAI-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/RadiologyAI-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="toolevalxm/RadiologyAI-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/RadiologyAI-TestRepo") model = AutoModelForImageClassification.from_pretrained("toolevalxm/RadiologyAI-TestRepo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 239c99a1e70527ca37644884ac1ac813e43fc804d54e341223558531125fc749
- Size of remote file:
- 42 Bytes
- SHA256:
- 0ff2b1279f9072443677469bd0543fa3cfb8bfa0ce5d40a98379981b632f102e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.