Instructions to use sharktide/FireTrustNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use sharktide/FireTrustNet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://sharktide/FireTrustNet") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| metrics: | |
| - mse | |
| library_name: keras | |
| This model requires the following custom objects: | |
| ```python | |
| import tensorflow as tf | |
| from tensorflow.keras.saving import register_keras_serializable | |
| from tensorflow.keras import layers, models, backend as K | |
| import numpy as np | |
| @register_keras_serializable() | |
| def firetrust_activation(x): | |
| return 0.5 + tf.sigmoid(x) # output in range [0.5, 1.5] | |
| ``` |