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
File size: 373 Bytes
ddda027 e6bdcf9 ddda027 bf07648 ddda027 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | 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)
CUSTOM_OBJECTS = {
"firetrust_activation": firetrust_activation,
"mse": tf.keras.losses.MeanSquaredError
}
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