Instructions to use pranav456/lesion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pranav456/lesion_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pranav456/lesion_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("pranav456/lesion_model") model = AutoModelForImageClassification.from_pretrained("pranav456/lesion_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pranav456/lesion_model: direct link, hf CLI and curl.
- Browser
- Download file 111 MB
-
https://huggingface.co/pranav456/lesion_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pranav456/lesion_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pranav456/lesion_model/resolve/main/pytorch_model.bin
111 MB
- Xet hash:
- fcb8e2444bef03f0aae6fcca3f901303dcadaeedfa37ddddd16a1a70dae19322
- Size of remote file:
- 111 MB
- SHA256:
- d20bee5793c093aa5cfcd75627e5ef92f19c969f35e99deb1fbe0750da1b8501
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