synthetics_config.py

# Create the Gretel Synthtetics Training / Model Configuration

from pathlib import Path
from gretel_helpers.synthetics import create_df, SyntheticDataBundle

config_template = {
    "epochs": 50,
    "early_stopping": False,
    "vocab_size": 20,
    "reset_states": False, 
    "checkpoint_dir": str(Path.cwd() / "checkpoints-sin"),
    "overwrite": True,
}

model = SyntheticDataBundle(
    training_df=trends_df,
    delimiter=",",
    auto_validate=True, 
    synthetic_config=config_template,
    header_prefix=['date'] # Seed the model with the date field
    )

model.build()
model.train()