Time Series Forecasting
TF-Keras
Joblib
Keras
fumd_migration_forecaster
vehicular-networks
cellular-handover
mobility-prediction
5g
v2x
lstm
bilstm
attention
bahdanau-attention
tensorflow
sumo
omnetpp
simu5g
simulation
Eval Results (legacy)
Instructions to use fumd-ai/handover-forecaster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use fumd-ai/handover-forecaster with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("fumd-ai/handover-forecaster") - Keras
How to use fumd-ai/handover-forecaster with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://fumd-ai/handover-forecaster") - Notebooks
- Google Colab
- Kaggle
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