Instructions to use aakashjapi/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use aakashjapi/temp with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://aakashjapi/temp") - Notebooks
- Google Colab
- Kaggle
| # Lambda Keras Model | |
| A minimal tf.keras model with a single Lambda layer that doubles the input. | |
| Input shape: (4,) | |
| Saved in Keras v3 .keras format. |