from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "gxinxing/qwen-trader-cn-merged"
model = AutoModelForCausalLM.from_pretrained(
    model_id, torch_dtype=torch.float16, device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_id)

prompt = "请分析今天的A股大盘走势"
messages = [{"role": "user", "content": prompt}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))

关联仓库

同架构英文/多市场交易微调版：gxinxing/qwen-trader-merged
LoRA 适配器：gxinxing/qwen-trader-cn-lora、gxinxing/qwen-trader-lora