Instructions to use FPSica/beyond-backscatter-grd-gee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use FPSica/beyond-backscatter-grd-gee with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://FPSica/beyond-backscatter-grd-gee") - Notebooks
- Google Colab
- Kaggle
Upload config.yaml with huggingface_hub
Browse files- config.yaml +1 -0
config.yaml
CHANGED
|
@@ -1,6 +1,7 @@
|
|
| 1 |
framework: tensorflow
|
| 2 |
framework_detail: tensorflow_keras
|
| 3 |
weights_filename: model.weights.h5
|
|
|
|
| 4 |
architecture:
|
| 5 |
name: resunet
|
| 6 |
implementation: src/colab_grd_gee/tf_model.py
|
|
|
|
| 1 |
framework: tensorflow
|
| 2 |
framework_detail: tensorflow_keras
|
| 3 |
weights_filename: model.weights.h5
|
| 4 |
+
weights_format: legacy_keras_h5
|
| 5 |
architecture:
|
| 6 |
name: resunet
|
| 7 |
implementation: src/colab_grd_gee/tf_model.py
|