
This is a Chinese instruction-tuning lora checkpoint based on llama-13B from [this repo's](https://github.com/Facico/Chinese-Vicuna) work

You can use it like this: 


```python
from transformers import LlamaForCausalLM
from peft import PeftModel

model = LlamaForCausalLM.from_pretrained(
    "decapoda-research/llama-13b-hf",
    load_in_8bit=True,
    torch_dtype=torch.float16,
    device_map="auto",
)
model = PeftModel.from_pretrained(
    model,
    LORA_PATH, # specific checkpoint path from "Chinese-Vicuna/Chinese-Vicuna-lora-13b-belle-and-guanaco"
    torch_dtype=torch.float16,
    device_map={'': 0}
)
```
{"language": ["zh", "en"], "license": "gpl-3.0", "datasets": ["BelleGroup/generated_train_0.5M_CN", "JosephusCheung/GuanacoDataset"]}
zh en dataset:BelleGroup/generated_train_0.5M_CN dataset:JosephusCheung/GuanacoDataset license:gpl-3.0 has_space region:us
TAGS
#zh #en #dataset-BelleGroup/generated_train_0.5M_CN #dataset-JosephusCheung/GuanacoDataset #license-gpl-3.0 #has_space #region-us 


This is a Chinese instruction-tuning lora checkpoint based on llama-13B from this repo's work

You can use it like this: 



TAGS
#zh #en #dataset-BelleGroup/generated_train_0.5M_CN #dataset-JosephusCheung/GuanacoDataset #license-gpl-3.0 #has_space #region-us 

TAGS
#zh #en #dataset-BelleGroup/generated_train_0.5M_CN #dataset-JosephusCheung/GuanacoDataset #license-gpl-3.0 #has_space #region-us 
