A company needs to reduce an FM adaptation job memory footprint while changing a limited set of model parameters. Which technique should be evaluated for supported frameworks?

1. Full retraining of every model weight from random initialization as the only option.
2. Removing all validation to save memory.
3. Changing only the model display name.
4. A supported parameter-efficient fine-tuning method such as LoRA.