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ChatGLM-6B
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Update loading instructions

pull/621/head
duzx16 2023-04-13 16:10:10 +08:00
parent 63b1e4e804
commit 5ade1e4055
2 changed files with 5 additions and 3 deletions
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3
ptuning/README.md
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@ -152,6 +152,7 @@ model = AutoModel.from_pretrained("THUDM/chatglm-6b", config=config, trust_remot
prefix_state_dict = torch.load(os.path.join(CHECKPOINT_PATH, "pytorch_model.bin"))
new_prefix_state_dict = {}
for k, v in prefix_state_dict.items():
if k.startswith("transformer.prefix_encoder."):
new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v
model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
```
@ -160,7 +161,7 @@ model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
(2) 如果需要加载的是旧 Checkpoint（包含 ChatGLM-6B 以及 PrefixEncoder 参数），或者进行的全参数微调，则直接加载整个 Checkpoint：
```python
model = AutoModel.from_pretrained(CHECKPOINT_PATH, config=config, trust_remote_code=True)
model = AutoModel.from_pretrained(CHECKPOINT_PATH, trust_remote_code=True)
```
之后根据需求可以进行量化，也可以直接使用：

1
ptuning/main.py
View File

@ -118,6 +118,7 @@ def main():
prefix_state_dict = torch.load(os.path.join(model_args.ptuning_checkpoint, "pytorch_model.bin"))
new_prefix_state_dict = {}
for k, v in prefix_state_dict.items():
if k.startswith("transformer.prefix_encoder."):
new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v
model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
else: