chat_completion.py

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

model_name_or_path = "/home/DeepSeek-V2/DeepSeek-V2-Lite-Chat"
# model_name_or_path = "deepseek-ai/DeepSeek-V2-Lite-Chat"

tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
model.generation_config = GenerationConfig.from_pretrained(model_name_or_path)
model.generation_config.pad_token_id = model.generation_config.eos_token_id

messages = [
    {"role": "user", "content": "Write a piece of quicksort code in C++"}
]
input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")
outputs = model.generate(input_tensor.to(model.device), max_new_tokens=100)

result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True)
print("result", result)