[Bugfix] Skip bias tensors in online FP8 quantization pipeline

[r266-tech]

Summary

Add "bias" to SKIP_TENSORS in vllm/model_executor/model_loader/reload/meta.py so bias parameters bypass make_online_process_loader wrapping during initialize_online_processing.

Problem: When using --quantization fp8 on BF16 checkpoints, models with bias=True linear layers (Qwen2/2.5, GPT-2, Phi, etc.) produce garbage output. The bias tensors get wrapped by the online processing pipeline but never materialize — they silently stay at zero.

Root cause: initialize_online_processing in layerwise.py wraps weight loaders for all tensors not in SKIP_TENSORS. Bias parameters (1D, small) don't need FP8 quantization and are not designed to flow through the deferred loading pipeline. Same class of bug as #37334 and #38746.

Fix: 1-line addition of "bias" to the skip set. All vllm parallel linear layers (ColumnParallelLinear, QKVParallelLinear, RowParallelLinear, etc.) register bias as self.bias via Parameter(...) or register_parameter("bias", None), so the exact string "bias" matches all standard bias parameters.

Note: Custom non-standard bias parameters with different names (e.g., e_score_correction_bias) are already individually listed in SKIP_TENSORS. This fix targets the standard nn.Linear-style bias that all parallel linear layers inherit.

Fixes #39663

[gemini-code-assist]

Code Review

This pull request updates the metadata keys in vllm/model_executor/model_loader/reload/meta.py by adding "bias" to the existing set. There are no review comments, and I have no feedback to provide.