【solved】use adpater_v2.py fine-tuning llama 13B error

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when i use alpaca data to fine-tuning llama13B on 4*A100 80GB GPU, i got the following erroes:
```
RuntimeError: Error(s) in loading state_dict for LLaMA:
size mismatch for lm_head.weight: copying a param with shape torch.Size([32000, 5120]) from checkpoint, the shape in current model is torch.Size([32000, 4096]).
size mismatch for transformer.wte.weight: copying a param with shape torch.Size([32000, 5120]) from checkpoint, the shape in current model is torch.Size([32000, 4096]).
size mismatch for transformer.h.0.rms_1.scale: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for transformer.h.0.attn.c_attn.weight: copying a param with shape torch.Size([15360, 5120]) from checkpoint, the shape in current model is torch.Size([12288, 4096]).
size mismatch for transformer.h.0.attn.c_proj.weight: copying a param with shape torch.Size([5120, 5120]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
size mismatch for transformer.h.0.rms_2.scale: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for transformer.h.0.mlp.c_fc1.weight: copying a param with shape torch.Size([13824, 5120]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
size mismatch for transformer.h.0.mlp.c_fc2.weight: copying a param with shape torch.Size([13824, 5120]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
size mismatch for transformer.h.0.mlp.c_proj.weight: copying a param with shape torch.Size([5120, 13824]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
size mismatch for transformer.h.1.rms_1.scale: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for transformer.h.1.attn.c_attn.weight: copying a param with shape torch.Size([15360, 5120]) from checkpoint, the shape in current model is torch.Size([12288, 4096]).
size mismatch for transformer.h.1.attn.c_proj.weight: copying a param with shape torch.Size([5120, 5120]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
size mismatch for transformer.h.1.rms_2.scale: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for transformer.h.1.mlp.c_fc1.weight: copying a param with shape torch.Size([13824, 5120]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
size mismatch for transformer.h.1.mlp.c_fc2.weight: copying a param with shape torch.Size([13824, 5120]) from checkpoint, the shape in current model is torch.Size([11008, 4096]).
size mismatch for transformer.h.1.mlp.c_proj.weight: copying a param with shape torch.Size([5120, 13824]) from checkpoint, the shape in current model is torch.Size([4096, 11008]).
size mismatch for transformer.h.2.rms_1.scale: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([4096]).
size mismatch for transformer.h.2.attn.c_attn.weight: copying a param with shape torch.Size([15360, 5120]) from checkpoint, the shape in current model is torch.Size([12288, 4096]).
size mismatch for transformer.h.2.attn.c_proj.weight: copying a param with shape torch.Size([5120, 5120]) from checkpoint, the shape in current model is torch.Size([4096, 4096]).
```

i'm sure i download the right version of llama13B, and i use the convert_hf_checkpoint.py to convert xx.bin to xx.ph

Start with adapter_v2.py and convert_hf_checkpoint.py, then compare the converted checkpoint's tensor shapes with the LLaMA 13B model configuration. Reproduce the state_dict loading error if possible; the issue provides no confirmed fix or clear completion criteria, and its title says it is solved.

Written by the indexing model from the issue text.