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fix torch_dtype on awq (#38463)

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Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
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jiqing-feng 2025-06-06 23:14:00 +08:00 committed by GitHub
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1 changed files with 4 additions and 4 deletions
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src/transformers/quantizers/quantizer_awq.py
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@ -92,11 +92,11 @@ class AwqQuantizer(HfQuantizer):
if torch_dtype is None: if torch_dtype is None:
torch_dtype = torch.float16 torch_dtype = torch.float16
logger.info("Loading the model in `torch.float16`. To overwrite it, set `torch_dtype` manually.") logger.info("Loading the model in `torch.float16`. To overwrite it, set `torch_dtype` manually.")
elif torch_dtype == torch.bfloat16: elif torch_dtype == torch.bfloat16 and torch.cuda.is_available():
logger.warning("`torch.bfloat16` is not supported for AWQ kernels yet. Casting to `torch.float16`.") logger.warning("`torch.bfloat16` is not supported for AWQ CUDA kernels yet. Casting to `torch.float16`.")
torch_dtype = torch.float16 torch_dtype = torch.float16
elif torch_dtype != torch.float16: elif torch_dtype != torch.float16 and torch.cuda.is_available():
logger.warning("We suggest you to set `torch_dtype=torch.float16` for better efficiency with AWQ.") logger.warning("We suggest you to set `torch_dtype=torch.float16` for better efficiency on CUDA with AWQ.")
return torch_dtype return torch_dtype
def _process_model_before_weight_loading( def _process_model_before_weight_loading(