Instructions to use parhamjanjan87/Tomur-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parhamjanjan87/Tomur-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="parhamjanjan87/Tomur-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("parhamjanjan87/Tomur-Classification") model = AutoModelForImageClassification.from_pretrained("parhamjanjan87/Tomur-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 595 Bytes
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tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: Tomur-Classification
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.989965886365442
---
# Tomur-Classification
## Example Images
#### glioma-tomur

#### hipofiz-tomur

#### meningioma-tumor

#### no-tomur
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