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We can serialize the weights of Neural VT and the samples gathered from that VT into one HDF5 file. This enhancement will allow us to use one file for two purposes. We must update the load_vt and save_model methods in the NeuralVT class.
The text was updated successfully, but these errors were encountered:
* feat: refactor model save/load functions to use h5py and remove hyperparameters
* feat: update samples_from_vt script to support HDF5 input/output and save model weights
* feat: update CI workflow to trigger on all branches and paths for Python files
* Revert "feat: update CI workflow to trigger on all branches and paths for Python files"
This reverts commit 4a54338.
* feat: enhance type hints and validation in train_regressor function
* feat: add utility functions for model handling and data processing
* feat: convenience class `NeuralVT`
* feat: update documentation and exports for gwkokab.vts module
* feat: refactor samples_from_vt.py to utilize NeuralVT for model handling
* refactor: `Parameter` class as a dataclass
We can serialize the weights of Neural VT and the samples gathered from that VT into one HDF5 file. This enhancement will allow us to use one file for two purposes. We must update the
load_vt
andsave_model
methods in theNeuralVT
class.The text was updated successfully, but these errors were encountered: