Instructions to use AndyWu0719/unet2dattentionmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AndyWu0719/unet2dattentionmodel 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://AndyWu0719/unet2dattentionmodel") - Notebooks
- Google Colab
- Kaggle
Space Path
If you want to try this model online, you can go space path: AndyWu0719/unet2dattention
UNet 2D Attention Model for MRI Tumor Segmentation
This repository contains a UNet 2D Attention model for MRI tumor segmentation.
Usage
To use this model, you can load it with the transformers library:
from transformers import AutoModel
model = AutoModel.from_pretrained("AndyWu0719/unet2dattentionmodel")
## Model Details
Model type: UNet 2D Attention
Task: MRI Tumor Segmentation
Framework: Tensorflow
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