alora_train(datafile: str = typer.Argument(..., help='JSONL file with item/label pairs'), basemodel: str = typer.Option(..., help='Base model ID or path'), outfile: str = typer.Option(..., help='Path to save adapter weights'), promptfile: str = typer.Option(None, help='Path to load the prompt format file'), adapter: str = typer.Option('alora', help='Adapter type: alora or lora'), epochs: int = typer.Option(6, help='Number of training epochs'), learning_rate: float = typer.Option(6e-06, help='Learning rate'), batch_size: int = typer.Option(2, help='Per-device batch size'), max_length: int = typer.Option(1024, help='Max sequence length'), grad_accum: int = typer.Option(4, help='Gradient accumulation steps'))

alora_upload(weightfile: str = typer.Argument(..., help='Path to saved adapter weights'), name: str = typer.Option(..., help='Destination model name (e.g., acme/carbchecker-alora)'))