gpt-fast KeyError: 'model.layers.{}.self_attn.W

device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), Model config {'block_size': 2048, 'vocab_size': 32000, 'n_layer': 32, 'n_head': 32, 'dim': 4096, 'intermediate_size': 11008, 'n_local_heads': 32, 'head_dim': 128, 'rope_base': 10000, 'norm_eps': 1e-05} /mnt/user/wangchenpeng/venv/fast/lib/python3.8/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() return self.fget.get(instance, owner)() Traceback (most recent call last): File "scripts/convert_hf_checkpoint.py", line 106, in convert_hf_checkpoint( File "/mnt/user/wangchenpeng/venv/fast/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "scripts/convert_hf_checkpoint.py", line 76, in convert_hf_checkpoint new_key = weight_map[abstract_key] KeyError: 'model.layers.{}.self_attn.W_pack.weight'