Instructions to use saeruig/brain_tumor_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saeruig/brain_tumor_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="saeruig/brain_tumor_classifier") 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("saeruig/brain_tumor_classifier") model = AutoModelForImageClassification.from_pretrained("saeruig/brain_tumor_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from saeruig/brain_tumor_classifier: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/saeruig/brain_tumor_classifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://saeruig/brain_tumor_classifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/saeruig/brain_tumor_classifier/resolve/main/optimizer.pt
687 MB
- Xet hash:
- 0f63f467e45582540eb983a13de85b2f6637ebd1a33fb453ce1344fdc4c313c3
- Size of remote file:
- 687 MB
- SHA256:
- a9a71e5517333d63a084d796b7175502023cc2118ee944f37f4b1475ee383f3d
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