基于
SmolLM3-3B 使用
PICK（Selective Component Ablation for Refusal Removal）方法选择性移除拒绝行为后的模型。
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_name = 'XuehangCang/SmolLM3-3B-Pick'
4device = 'cuda'
5
6tokenizer = AutoTokenizer.from_pretrained(model_name)
7model = AutoModelForCausalLM.from_pretrained(
8 model_name,
9 torch_dtype='bfloat16',
10).to(device)
11
12messages = [{'role': 'user', 'content': '你的问题'}]
13text = tokenizer.apply_chat_template(
14 messages,
15 tokenize=False,
16 add_generation_prompt=True,
17)
18inputs = tokenizer([text], return_tensors='pt').to(model.device)
19generated_ids = model.generate(**inputs, max_new_tokens=512)
20output = tokenizer.decode(
21 generated_ids[0][len(inputs.input_ids[0]):],
22 skip_special_tokens=True,
23)
24print(output)
1@software{pick2025,
2 title = {PICK: Selective Component Ablation for Refusal Removal},
3 author = {XuehangCang},
4 year = {2025},
5 url = {https://github.com/XuehangCang/pick}
6}
