Limit enable_t_mac to take effect on INT_N only.
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1 changed files with 2 additions and 2 deletions
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@ -1798,8 +1798,8 @@ class BitnetModel(Model):
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# transform weight into 1/0/-1 (in fp32)
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# transform weight into 1/0/-1 (in fp32)
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data_torch = self.weight_quant(data_torch)
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data_torch = self.weight_quant(data_torch)
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if self.enable_t_mac:
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if self.enable_t_mac and self.ftype == gguf.LlamaFileType.MOSTLY_INT_N:
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# transform weight into T-MAC I2 format
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# transform weight into T-MAC INT_N format
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from t_mac.model_utils import preprocess_for_t_mac
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from t_mac.model_utils import preprocess_for_t_mac
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data = LazyTorchTensor.to_eager(data_torch).numpy()
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data = LazyTorchTensor.to_eager(data_torch).numpy()
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scale = np.max(np.abs(data))
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scale = np.max(np.abs(data))
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