---
datasets:
- wikitext-2-v1
- yizhongw/self_instruct
language:
- en
library_name: transformers
metrics: crossentropy
---

1. download the pth file
2. load the state dict

```python
from transformers import T5Tokenizer
from transformers.models.llama import LlamaConfig

config = LlamaConfig.from_pretrained(f"hpcaitech/openmoe-base")
model = OpenMoeForCausalLM(config)
ckpt = torch.load("openmoe_base_yizhongw_super_natural_instruction_generation.pth")
state_dict = {}
for key, value in ckpt.items():
    if key.startswith("module."):
        state_dict[key[7:]] = value
    else:
        state_dict[key] = value
model.load_state_dict(state_dict)
```