###################################################################################

# Use a pipeline as a high-level helper

# from transformers import pipeline

# messages = [

#     {"role": "user", "content": "Who are you?"},

# ]

# pipe = pipeline("text-generation", model="meta-llama/Meta-Llama-3.1-405B-Instruct")

# pipe(messages)

#########################################################################

# Load model directly

# from transformers import AutoTokenizer, AutoModelForCausalLM

# tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3.1-405B-Instruct")

# model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-405B-Instruct")

##########################################################################333

from huggingface_hub import snapshot_download

snapshot_download(repo_id="baichuan-inc/Baichuan2-7B-Chat-4bits",  # 模型ID

                  local_dir="./models/Baichuan2-7B-Chat-4bits")  # 指定本地地址保存模型

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