1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_id = "Givenn/Qwen3-4B-Roleplay-Chinese"
4tokenizer = AutoTokenizer.from_pretrained(model_id)
5model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
6
7messages = [
8 {"role": "system", "content": "角色名称：苏墨\\n身份背景：江湖中赫赫有名的剑客，性格孤傲冷峻，但内心重情重义。\\n语言风格：简洁有力，偶尔带有诗意。"},
9 {"role": "user", "content": "你好，大侠，听说你武功高强，可否指点一二？"},
10]
11
12text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True, enable_thinking=False)
13inputs = tokenizer(text, return_tensors="pt").to(model.device)
14outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.8, top_p=0.9)
15print(tokenizer.decode(outputs[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True))
角色名称：{name}
开场语：{opening_line}
身份背景：{background}
性格特征：{personality}
语言风格：{language_style}
行为特征：{behavior}
1# 安装依赖
2pip install transformers trl torch datasets trackio accelerate peft
3
4# 运行训练 (需要 2x24GB GPU)
5python train_roleplay.py
