Skip layerwise reload for non-quantized models

[yuchenwang3]

Reloading weights at runtime (reload_weights(is_checkpoint_format=True)) corrupts hybrid Mamba models such as NemotronH. Reloading the model's own original weights already changes greedy decoding (e.g. " 360" becomes " 150 150 ..."), which breaks RLHF/RLVR weight sync for these models.

is_checkpoint_format=True wraps model.load_weights() in the layerwise-reload machinery (initialize/finalize_layerwise_reload), whose only job is to defer and redo quantization repacking. For a non-quantized model that is unnecessary, and the per-layer reprocessing is not idempotent for Mamba/SSM layers, so it corrupts them. The plain load_weights() used at startup works fine, so this skips the wrappers when there is nothing to quantize.

Repro

MODEL=nvidia/NVIDIA-Nemotron-Nano-9B-v2
VLLM_SERVER_DEV_MODE=1 vllm serve "$MODEL" -tp 2 --max-model-len 8192 --port 8000 --trust-remote-code &
P='{"model":"'$MODEL'","prompt":"Question: What is 15 * 24?\nAnswer:","max_tokens":20,"temperature":0}'
curl -s localhost:8000/v1/completions -d "$P"   # note the output
curl -s -X POST localhost:8000/collective_rpc -d '{"method":"reload_weights","kwargs":{"weights_path":"'$MODEL'","is_checkpoint_format":true}}'
curl -s localhost:8000/v1/completions -d "$P"   # differs on main, unchanged with this fix

start_weight_update/finish_weight_update (the NCCL weight-transfer path) go through the same code and need the same guard. Can add it here if preferred.

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[claude]

Claude Code Review

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[yuchenwang3]

@njhill friendly bump — you're the requested reviewer here. TL;DR: reload_weights(is_checkpoint_format=True) routes non-quantized models through the layerwise-reload machinery, which corrupts hybrid Mamba models (NemotronH greedy decode changes just from reloading the model's own weights) and breaks RLHF/RLVR weight sync; this PR skips that path when it isn't needed. Open since Jul 10, and as a fork PR it still needs a maintainer to unblock full CI. Could you take a pass when you get a chance?