Instructions to use Kaynaaf/BrainMRI-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Kaynaaf/BrainMRI-Classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Kaynaaf/BrainMRI-Classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -50,7 +50,7 @@ Finetune the model on other diagnostic scans, though the model only accepts gray
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| **Macro Avg** | 0.90 | 0.89 | 0.89 | 1311 |
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| **Weighted Avg** | 0.90 | 0.90 | 0.90 | 1311 |
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### Results
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This model was developed for my project that can be found on github [here](https://github.com/Kaynaaf/BrainMRI-Classifier)
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. This project involved generating sensitivity maps to explain the predictions of the model.
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| **Macro Avg** | 0.90 | 0.89 | 0.89 | 1311 |
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| **Weighted Avg** | 0.90 | 0.90 | 0.90 | 1311 |
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### Results
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This model was developed for my project that can be found on github [here](https://github.com/Kaynaaf/BrainMRI-Classifier)
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. This project involved generating sensitivity maps to explain the predictions of the model.
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