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py : fix position embeddings chop [no ci]

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Georgi Gerganov 2024-09-17 13:53:19 +03:00
parent 77723ed69e
commit 49f90de363
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1 changed files with 5 additions and 5 deletions
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convert_hf_to_gguf.py
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@ -2701,16 +2701,16 @@ class XLMRobertaModel(BertModel):
self.gguf_writer.add_add_eos_token(True) self.gguf_writer.add_add_eos_token(True)
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]]:
# position embeddings start at pad_token_id + 1, so just chop down the weight tensor
if name == "embeddings.position_embeddings.weight":
if self._position_offset is not None:
data_torch = data_torch[self._position_offset:,:]
# if name starts with "roberta.", remove the prefix # if name starts with "roberta.", remove the prefix
# e.g. https://huggingface.co/BAAI/bge-reranker-v2-m3/tree/main # e.g. https://huggingface.co/BAAI/bge-reranker-v2-m3/tree/main
if name.startswith("roberta."): if name.startswith("roberta."):
name = name[8:] name = name[8:]
# position embeddings start at pad_token_id + 1, so just chop down the weight tensor
if name == "embeddings.position_embeddings.weight":
if self._position_offset is not None:
data_torch = data_torch[self._position_offset:,:]
return super().modify_tensors(data_torch, name, bid) return super().modify_tensors(data_torch, name, bid)