return tensors
prefix = "model" if not self.is_mistral_format else "consolidated"
- part_names: set[str] = set(ModelBase.get_model_part_names(self.dir_model, prefix, ".safetensors"))
+ part_names: list[str] = ModelBase.get_model_part_names(self.dir_model, prefix, ".safetensors")
is_safetensors: bool = len(part_names) > 0
if not is_safetensors:
- part_names = set(ModelBase.get_model_part_names(self.dir_model, "pytorch_model", ".bin"))
+ part_names = ModelBase.get_model_part_names(self.dir_model, "pytorch_model", ".bin")
tensor_names_from_index: set[str] = set()
if weight_map is None or not isinstance(weight_map, dict):
raise ValueError(f"Can't load 'weight_map' from {index_name!r}")
tensor_names_from_index.update(weight_map.keys())
- part_names |= set(weight_map.values())
+ part_dict: dict[str, None] = dict.fromkeys(weight_map.values(), None)
+ part_names = sorted(part_dict.keys())
else:
weight_map = {}
else: