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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 14, 05:30 UTC

[Feature][Quantization] auto_round support for mixed bits quantization (#23812)

Signed-off-by: n1ck-guo <heng.guo@intel.com> Signed-off-by: Heng Guo <heng.guo@intel.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

Heng Guo committed Oct 21, 2025 at 06:23 UTC 87778d5f00ab09f88d0b677c34ae7d33e6296ce2
1 file changed +6
vllm/model_executor/layers/quantization/auto_round.py
+6
@@ -436,6 +436,12 @@ class AutoRoundConfig(QuantizationConfig):
436 return None
437
438 def get_quant_method(self, layer: torch.nn.Module, prefix: str):
439 + if prefix and self.extra_config:
440 + for layer_name in self.extra_config:
441 + if (
442 + layer_name == prefix or layer_name == f"model.{prefix}"
443 + ) and self.extra_config[layer_name].get("bits", 16) >= 16:
444 + return UnquantizedLinearMethod()
445 if (
446 current_platform.is_cpu()
447 or current_platform.is_xpu()