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fix(mlx-lm): handle legacy quant models (#369)

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Anchen 2024-01-25 02:44:05 +11:00 committed by GitHub
parent ab91ac1075
commit 5fc8668a53
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1 changed files with 19 additions and 5 deletions
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24
llms/mlx_lm/utils.py
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@ -226,11 +226,25 @@ def load_model(model_path: Path) -> nn.Module:
model = model_class(model_args) model = model_class(model_args)
if quantization is not None: if quantization is not None:
nn.QuantizedLinear.quantize_module( # for legacy models that don't have lm_head quant due to non-32 dims
model, if "lm_head.scales" not in weights.keys():
**quantization, vocab_size = config["vocab_size"]
linear_class_predicate=linear_class_predicate, extended_linear_class_predicate = (
) lambda layer: linear_class_predicate(layer)
and layer.weight.shape[0] != vocab_size
)
nn.QuantizedLinear.quantize_module(
model,
**quantization,
linear_class_predicate=extended_linear_class_predicate,
)
# for models that have lm_head quant
else:
nn.QuantizedLinear.quantize_module(
model,
**quantization,
linear_class_predicate=linear_class_predicate,
)
model.load_weights(list(weights.items())) model.load_weights(list(weights.items()))