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:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Kaynaaf/BrainMRI-Classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -53,7 +53,8 @@ Finetune the model on other diagnostic scans, though the model only accepts gray
|
|
| 53 |
|
| 54 |
### Results
|
| 55 |
This model was developed for my project that can be found on github [here](https://github.com/Kaynaaf/BrainMRI-Classifier)
|
| 56 |
-
|
|
|
|
| 57 |

|
| 58 |

|
| 59 |
|
|
|
|
| 53 |
|
| 54 |
### Results
|
| 55 |
This model was developed for my project that can be found on github [here](https://github.com/Kaynaaf/BrainMRI-Classifier)
|
| 56 |
+
This project involved generating sensitivity maps to explain the predictions of the model.
|
| 57 |
+
These maps assign values to areas of the image that act as feature importance markers.
|
| 58 |

|
| 59 |

|
| 60 |
|