Instructions to use Devarshi/Brain_Tumor_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devarshi/Brain_Tumor_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Devarshi/Brain_Tumor_Classification") 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("Devarshi/Brain_Tumor_Classification") model = AutoModelForImageClassification.from_pretrained("Devarshi/Brain_Tumor_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Devarshi/Brain_Tumor_Classification: direct link, hf CLI and curl.
- Browser
- Download file 110 MB
-
https://huggingface.co/Devarshi/Brain_Tumor_Classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Devarshi/Brain_Tumor_Classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Devarshi/Brain_Tumor_Classification/resolve/main/pytorch_model.bin
110 MB
- Xet hash:
- 0582fe2404dd14549ddedd98b10e621e26b506655c5db1fbac54cdee664f19eb
- Size of remote file:
- 110 MB
- SHA256:
- aa057f5f4594c8baa83623ad82e194d4139d97e45f0254a73cca2fdfc1b05218
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