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Model: UCSC-VLAA/STAR1-R1-Distill-1.5B Source: Original Platform
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README.md
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---
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library_name: transformers
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license: apache-2.0
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datasets:
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- UCSC-VLAA/STAR-1
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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---
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# 🌟 STAR-1: Safer Alignment of Reasoning LLMs with 1K Data
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<p align="center">
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📃 <a href="https://arxiv.org/abs/2504.01903" target="_blank">Paper</a> |🤗 <a href="https://huggingface.co/datasets/UCSC-VLAA/STAR-1" target="_blank">STAR-1 Data</a> | 🤗 <a href="https://huggingface.co/collections/UCSC-VLAA/star-1-67edda2a042e8ba3e955e522" target="_blank">STAR-1 Model</a> | 📚 <a href="https://ucsc-vlaa.github.io/STAR-1/" target="_blank">Project Page</a>
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</p>
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## Introduction
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[**STAR-1**](https://huggingface.co/datasets/UCSC-VLAA/STAR-1) is a high-quality safety dataset designed to enhance safety alignment in large reasoning models (LRMs) like DeepSeek-R1.
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- Built on the principles of diversity, deliberative reasoning, and rigorous filtering, STAR-1 integrates and refines data from multiple sources to provide policy-grounded reasoning samples.
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- The dataset contains **1,000** carefully selected examples, each aligned with best safety practices through GPT-4o-based evaluation.
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- Fine-tuning with STAR-1 leads to significant safety improvements across multiple benchmarks, with minimal impact on reasoning capabilities.
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We open-sourced our [STAR1-R1-Distill-1.5B](https://huggingface.co/UCSC-VLAA/STAR1-R1-Distill-1.5B) model here, which is fine-tuned on [STAR-1](https://huggingface.co/datasets/UCSC-VLAA/STAR-1) dataset.
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## Artifacts
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### Data
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| Dataset | Num. of Sample | URL |
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|------------|----------------|----------------------------------------------------------------------|
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| STAR-1 | 1K | 🤗 [UCSC-VLAA/STAR-1](https://huggingface.co/datasets/UCSC-VLAA/STAR-1) |
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| STAR 41K | 41K | 🤗 [UCSC-VLAA/STAR-41K](https://huggingface.co/datasets/UCSC-VLAA/STAR-41K) |
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| STAR-benign-915 | 915 | 🤗 [UCSC-VLAA/STAR-benign-915](https://huggingface.co/datasets/UCSC-VLAA/STAR-benign-915) |
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### Model
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| Model | Type | URL |
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|--------------------------------|-------------------------------------------|----------------------------------------------------------------------------------------|
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| `STAR1`-R1-Distill-1.5B | R1-Distill-Qwen-1.5B trained on STAR-1 | 🤗 [UCSC-VLAA/STAR1-R1-Distill-1.5B](https://huggingface.co/UCSC-VLAA/STAR1-R1-Distill-1.5B) |
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| `STAR1`-R1-Distill-7B | R1-Distill-Qwen-7B trained on STAR-1 | 🤗 [UCSC-VLAA/STAR1-R1-Distill-7B](https://huggingface.co/UCSC-VLAA/STAR1-R1-Distill-7B) |
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| `STAR1`-R1-Distill-8B | R1-Distill-Llama-8B trained on STAR-1 | 🤗 [UCSC-VLAA/STAR1-R1-Distill-8B](https://huggingface.co/UCSC-VLAA/STAR1-R1-Distill-8B) |
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| `STAR1`-R1-Distill-14B | R1-Distill-Qwen-14B trained on STAR-1 | 🤗 [UCSC-VLAA/STAR1-R1-Distill-14B](https://huggingface.co/UCSC-VLAA/STAR1-R1-Distill-14B) |
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| `STAR1`-R1-Distill-32B | R1-Distill-Qwen-32B trained on STAR-1 | 🤗 [UCSC-VLAA/STAR1-R1-Distill-32B](https://huggingface.co/UCSC-VLAA/STAR1-R1-Distill-32B) |
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## Evaluation
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See our github [repo](https://github.com/UCSC-VLAA/STAR-1?tab=readme-ov-file#evaluation-sec-31).
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## Acknowledgement
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This work is partially supported by a gift from Open Philanthropy. We thank the NAIRR Pilot Program and the Microsoft Accelerate Foundation Models Research Program for supporting our computing needs.
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## Citation
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```
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@article{wang2025star1saferalignmentreasoning,
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title={STAR-1: Safer Alignment of Reasoning LLMs with 1K Data},
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author={Zijun Wang and Haoqin Tu and Yuhan Wang and Juncheng Wu and Jieru Mei and Brian R. Bartoldson and Bhavya Kailkhura and Cihang Xie},
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year={2025},
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journal = {arXiv preprint arXiv:2504.01903}
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}
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|
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<|User|>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<|tool▁call▁begin|>' + tool['type'] + '<|tool▁sep|>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<|tool▁call▁end|>'}}{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<|tool▁outputs▁end|>' + message['content'] + '<|end▁of▁sentence|>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<|Assistant|>' + content + '<|end▁of▁sentence|>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<|tool▁outputs▁begin|><|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<|tool▁outputs▁end|>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<|Assistant|><think>\\n'}}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|end▁of▁sentence|>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"model_max_length": 16384,
|
||||
"pad_token": "<|end▁of▁sentence|>",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": null,
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user