Building the INT8 DiT needed ~42 GB because it materialised the bf16 model
first; loading it needed ~55 GB for the same reason, plus every shard
accumulated into one dict and then copied in. Both took the host down.

Both now stream. The quantiser reads tensors one at a time through safe_open
and flushes 4 GB shards, enumerating the Linear layers on a meta-device
skeleton instead of a real model. _load_quantized_base_dit builds its skeleton
on meta too, then assigns each shard into it as it is read.

Measured on the 13.6B DiT: 51 GB bf16 -> 13.6 GB INT8, ~4 GB peak to write,
and the load is 20 s at 0.6 GB RSS (safetensors mmap) with all 437 quantised
Linears present and nothing stranded on meta.

A checkpoint that leaves tensors on the meta device is now an error naming
them, rather than a model that fails later somewhere unrelated.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QXD9yKKFZHAB9t1LfWQWwz