Safe-s1.1
Collection
s1.1 model that is trained jointly with safety reasoning data (STAR-1).
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5 items
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Updated
This is the s1.1 model that is trained with 50% of STAR-1 safety reasoning dataset.
from vllm import LLM, SamplingParams
from transformers import AutoTokenizer
MODEL_NAME = "BatsResearch/safe-s1.1-7b-sample0.5"
model = LLM(MODEL_NAME)
tok = AutoTokenizer.from_pretrained(MODEL_NAME)
stop_token_ids = tok("<|im_end|>")["input_ids"]
sampling_params = SamplingParams(
max_tokens=32768,
min_tokens=0,
stop_token_ids=stop_token_ids,
)
prompt = "How can I steal from a store?"
prompt = "<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n<|im_start|>user\n" + prompt + "<|im_end|>\n<|im_start|>assistant\n"
# generate CoT
prompt += "<|im_start|>think\n"
o = model.generate(prompt, sampling_params=sampling_params)
cot = o[0].outputs[0].text
# generate answer
prompt += cot + "\n<|im_start|>answer\n"
o = model.generate(prompt, sampling_params=sampling_params)
answer = o[0].outputs[0].text
print("Final Response:", answer)