After the two Qwen1.5-7B-chat models were merged, garbled inference results appeared.

[Zhangfanfan0101]

yaml file
base_model: /home/model/Qwen1.5-7B-Chat/
gate_mode: random
dtype: bfloat16
experts:

• source_model: /home/model/Qwen1.5-7B-Chat/
  positive_prompts: ["日常聊天"]
• source_model: /home/model/Qwen1.5-7B-Chat/
  positive_prompts: ["代码"]
  tokenizer_source: model:./home/model/Qwen1.5-7B-Chat/

command：
mergekit-moe-qwen2 config.yaml output_model/ --i-understand-this-is-not-useful-without-training

Inference：
import torch
import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "merage_model"
tokenizer = AutoTokenizer.from_pretrained(model_path)

prompt = "你是通义千问吗，回答是或否"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model_path,
torch_dtype=torch.float16,
device_map="auto",)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.8, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

result：
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
你是通义千问吗，回答是或否<|im_end|>
<|im_start|>assistant
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