Fine-tune public Encodon

Use --pretrained_ckpt_path for public v1. Do not substitute --checkpoint_path: the public runner does not forward that argument to the fine-tuning task.

Instructions

Resolve the target label, dataset, checkpoint, and output directory from the request and available files. Reuse existing data and weights. For training, check the project's ML dependencies and a compatible NVIDIA GPU before launch. If a required resource is unavailable, complete the available data preparation and return the command with the missing prerequisite clearly identified. When training is requested and the prerequisites are met, execute it and check the resulting checkpoints and metrics. A request for preparation ends with the validated inputs and command.