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")# 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
| { | |
| "epoch": 4.99, | |
| "eval_accuracy": 0.9646761984861227, | |
| "eval_f1": 0.9646761984861227, | |
| "eval_loss": 0.10117336362600327, | |
| "eval_precision": 0.9646761984861227, | |
| "eval_recall": 0.9646761984861227, | |
| "eval_runtime": 60.8804, | |
| "eval_samples_per_second": 19.53, | |
| "eval_steps_per_second": 0.624 | |
| } |