Merging, evaluating and serving fine-tuned models and adapters

Combine models with weight averaging and task vectors (runnable), evaluate a fine-tune against baselines and for regressions, quantise and package it, serve many LoRA adapters on one base model, memory arithmetic, versioning and rollout.