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lora : raise error if lm_head is ignored (#9103)

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* lora : raise error if lm_head is ignored

* fix style

* clarify comment
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Xuan Son Nguyen 2024-09-12 13:33:57 +02:00 committed by GitHub
parent 2a825116b6
commit d4c3c10fad
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convert_lora_to_gguf.py
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@ -363,7 +363,13 @@ if __name__ == '__main__':
yield (name, cast(torch.Tensor, LoraTorchTensor(tensor.A, tensor.B))) yield (name, cast(torch.Tensor, LoraTorchTensor(tensor.A, tensor.B)))
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]: def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None) -> Iterable[tuple[str, Tensor]]:
dest = super().modify_tensors(data_torch, name, bid) dest = list(super().modify_tensors(data_torch, name, bid))
# some archs may have the same tensor for lm_head and output (tie word embeddings)
# in this case, adapters targeting lm_head will fail when using llama-export-lora
# therefore, we ignore them for now
# see: https://github.com/ggerganov/llama.cpp/issues/9065
if name == "lm_head.weight" and len(dest) == 0:
raise ValueError("lm_head is present in adapter, but is ignored in base model")
for dest_name, dest_data in dest: for dest_name, dest_data in dest:
assert isinstance(dest_data, LoraTorchTensor) assert isinstance(dest_data, LoraTorchTensor)
lora_a, lora_b = dest_data.get_lora_A_B() lora_a, lora_b = dest_data.get_lora_A_B()