Instructions to use NeuronZero/MRI-Reader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuronZero/MRI-Reader with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NeuronZero/MRI-Reader") 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("NeuronZero/MRI-Reader") model = AutoModelForImageClassification.from_pretrained("NeuronZero/MRI-Reader", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from NeuronZero/MRI-Reader: direct link, hf CLI and curl.
- Browser
- Download file 348 MB
-
https://huggingface.co/NeuronZero/MRI-Reader/resolve/main/model.safetensors
- Command line
-
hf download hf://NeuronZero/MRI-Reader/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/NeuronZero/MRI-Reader/resolve/main/model.safetensors
348 MB
- Xet hash:
- 865e5d8fcd2a0dae3847b71d6d3c8cec3c5a9453c953a874fa09be4e847c77ea
- Size of remote file:
- 348 MB
- SHA256:
- 8350bae2d69a0f757abcec1eb625852f70158166c989f9418b0c6ee529bea0f4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.