README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - tensorflow
  - keras
  - computer-vision
  - medical-imaging
  - brain-tumor
  - mobilevit
  - image-classification
datasets:
  - brain-tumor-mri
metrics:
  - accuracy
model-index:
  - name: MobileViT Brain Tumor Classifier
    results:
      - task:
          type: image-classification
          name: Brain Tumor Classification
        dataset:
          type: brain-tumor-mri
          name: Brain Tumor MRI Images
        metrics:
          - type: accuracy
            value: 0.985
            name: Accuracy

MobileViT Brain Tumor Classifier

This MobileViT model classifies brain MRI scans into:

• Healthy
• Tumor

Accuracy: 98.5%

⚠️ Note: For research/educational purposes only. Not for clinical use.

Model Files

• model.keras: Native Keras format (recommended)
• model.h5: Legacy H5 format
• saved_model/: TensorFlow SavedModel format
• model.weights.h5: Model weights only
• model_config.json: Model architecture configuration
• class_names.json: Class label mappings

Usage

import tensorflow as tf
from huggingface_hub import hf_hub_download

# Download and load model
model_path = hf_hub_download(repo_id="abdo1176/brain-model-test", filename="model.keras")
model = tf.keras.models.load_model(model_path)

# Or load weights only
weights_path = hf_hub_download(repo_id="abdo1176/brain-model-test", filename="model.weights.h5")
# model.load_weights(weights_path)