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Auto handle tied weights with new transformers

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Disty0
2025-11-27 18:24:55 +03:00
parent 6dae83c651
commit ff4c254930
1 changed files with 12 additions and 7 deletions
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modules/sdnq/loader.py
+12 -7
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@@ -130,13 +130,18 @@ def load_sdnq_model(model_path: str, model_cls: ModelMixin = None, file_name: st
state_dict = load_files(files, key_mapping=key_mapping, device=device, method=load_method)
if model.__class__.__name__ in {"T5EncoderModel", "UMT5EncoderModel"} and "encoder.embed_tokens.weight" not in state_dict.keys():
state_dict["encoder.embed_tokens.weight"] = state_dict["shared.weight"]
# Handle Qwen models with tied lm_head weights
if model.__class__.__name__ in {"Qwen3ForCausalLM"} and "lm_head.weight" not in state_dict.keys():
if "model.embed_tokens.weight" in state_dict.keys():
state_dict["lm_head.weight"] = state_dict["model.embed_tokens.weight"]
if isinstance(getattr(model, "_tied_weights_keys", None), dict):
for key, value in model._tied_weights_keys.items():
print(key, value)
if value in state_dict.keys() and key not in state_dict.keys():
state_dict[key] = state_dict[value]
else:
# older transformers case, handle known models manually
if model.__class__.__name__ in {"T5EncoderModel", "UMT5EncoderModel"} and "encoder.embed_tokens.weight" not in state_dict.keys():
state_dict["encoder.embed_tokens.weight"] = state_dict["shared.weight"]
elif model.__class__.__name__ in {"Qwen3ForCausalLM"} and "lm_head.weight" not in state_dict.keys():
if "model.embed_tokens.weight" in state_dict.keys():
state_dict["lm_head.weight"] = state_dict["model.embed_tokens.weight"]
model.load_state_dict(state_dict, assign=True)
del state_dict