Instructions to use keras-io/ProbabalisticBayesianModel-Wine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use keras-io/ProbabalisticBayesianModel-Wine with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras-io/ProbabalisticBayesianModel-Wine") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -26,6 +26,8 @@ The training was done using TensorFlow 2.8.0 and TensorFlow Probability 0.16.0.
|
|
| 26 |
|
| 27 |
### Training hyperparameters
|
| 28 |
|
| 29 |
-
|
| 30 |
-
-
|
| 31 |
-
-
|
|
|
|
|
|
|
|
|
| 26 |
|
| 27 |
### Training hyperparameters
|
| 28 |
|
| 29 |
+
| Optimizer | learning_rate | decay | rho | momentum | epsilon | centered | training_precision |
|
| 30 |
+
|----|-------------|-----|------|------|-------|-------|------------------|
|
| 31 |
+
|RMSprop|0.001|0.0|0.9|0.0|1e-07|False|float32|
|
| 32 |
+
|
| 33 |
+
|