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 pytorch_model.bin from saeruig/brain_tumor_classifier: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/saeruig/brain_tumor_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://saeruig/brain_tumor_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/saeruig/brain_tumor_classifier/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- fd077c6d2d7990c664329c4b32569d2a9e44a5eabafb1b8a48e9f4addf46eb78
- Size of remote file:
- 343 MB
- SHA256:
- 7126559680b5da598ef35b340e81afb31317f736d91303fc15ace7717d0f8ff5
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