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@@ -4,7 +4,7 @@ license_name: openmdw
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  license_link: LICENSE
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  ---
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  # Seed-X-Instruct-7B
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- <a href="https://github.com/ByteDance-Seed/Seed-X-7B/blob/main/Technical_Report.pdf">
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  <img src="https://img.shields.io/badge/Seed--X-Report-blue"></a>
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  <a href="https://huggingface.co/ByteDance-Seed/Seed-X-Instruct-7B">
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  <img src="https://img.shields.io/badge/Seed--X-Hugging Face-brightgreen"></a>
@@ -44,7 +44,7 @@ This repo contains the **Seed-X-Instruct** model, with the following features:
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  ## Quickstart
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  Here is a simple example demonstrating how to load the model and perform translation using ```vllm```
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  ```python
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- from vllm import LLM, SamplingParams
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  model_path = "./ByteDance-Seed/Seed-X-Instruct-7B"
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@@ -59,13 +59,13 @@ messages = [
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  "Translate the following English sentence into Chinese and explain it in detail:\nMay the force be with you <zh>" # with CoT
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  ]
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  # Sampling
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  decoding_params = SamplingParams(temperature=0,
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  max_tokens=512,
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  skip_special_tokens=True)
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- # Beam Search
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- decoding_params = BeamSearchParams(beam_width=4,
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- max_tokens=512)
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  results = model.generate(messages, decoding_params)
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  responses = [res.outputs[0].text.strip() for res in results]
@@ -75,21 +75,21 @@ print(responses)
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  ## Evaluation
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  We evaluated Seed-X on a diverse set of translation benchmarks, including FLORES-200, WMT-25, and a publicly released [challenge set](https://github.com/ByteDance-Seed/Seed-X-7B/tree/main/challenge_set) accompanied by human evaluations.
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  ![humen_eval](imgs/humen_eval.png)
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- For detailed benchmark results and analysis, please refer to our [Technical Report](https://github.com/ByteDance-Seed/Seed-X-7B/blob/main/Technical_Report.pdf).
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  ## License
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  This project is licensed under OpenMDW. See the [LICENSE](https://github.com/ByteDance-Seed/Seed-X-7B/blob/main/LICENSE.openmdw) file for details.
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  ## Citation
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- <!--If you find Seed-X useful for your research and applications, feel free to give us a star ⭐ or cite us using:
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  ```bibtex
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- @Article{XXX,
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- title={XXXXXXXXXXX},
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- author={XXX,XXX,XXX,XXX},
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  year={2025},
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- eprint={XXXX.XXXXX},
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  archivePrefix={arXiv},
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- primaryClass={cs.XX}
 
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  }
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- ```-->
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- We will soon publish our technical report on Arxiv.
 
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  license_link: LICENSE
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  ---
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  # Seed-X-Instruct-7B
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+ <a href="https://arxiv.org/pdf/2507.13618">
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  <img src="https://img.shields.io/badge/Seed--X-Report-blue"></a>
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  <a href="https://huggingface.co/ByteDance-Seed/Seed-X-Instruct-7B">
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  <img src="https://img.shields.io/badge/Seed--X-Hugging Face-brightgreen"></a>
 
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  ## Quickstart
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  Here is a simple example demonstrating how to load the model and perform translation using ```vllm```
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  ```python
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+ from vllm import LLM, SamplingParams, BeamSearchParams
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  model_path = "./ByteDance-Seed/Seed-X-Instruct-7B"
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  "Translate the following English sentence into Chinese and explain it in detail:\nMay the force be with you <zh>" # with CoT
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  ]
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+ # Beam Search
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+ decoding_params = BeamSearchParams(beam_width=4,
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+ max_tokens=512)
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  # Sampling
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  decoding_params = SamplingParams(temperature=0,
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  max_tokens=512,
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  skip_special_tokens=True)
 
 
 
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  results = model.generate(messages, decoding_params)
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  responses = [res.outputs[0].text.strip() for res in results]
 
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  ## Evaluation
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  We evaluated Seed-X on a diverse set of translation benchmarks, including FLORES-200, WMT-25, and a publicly released [challenge set](https://github.com/ByteDance-Seed/Seed-X-7B/tree/main/challenge_set) accompanied by human evaluations.
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  ![humen_eval](imgs/humen_eval.png)
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+ For detailed benchmark results and analysis, please refer to our [Technical Report](https://arxiv.org/pdf/2507.13618).
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  ## License
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  This project is licensed under OpenMDW. See the [LICENSE](https://github.com/ByteDance-Seed/Seed-X-7B/blob/main/LICENSE.openmdw) file for details.
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  ## Citation
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+ If you find Seed-X useful for your research and applications, feel free to give us a star ⭐ or cite us using:
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  ```bibtex
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+ @misc{cheng2025seedxbuildingstrongmultilingual,
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+ title={Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters},
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+ author={Shanbo Cheng and Yu Bao and Qian Cao and Luyang Huang and Liyan Kang and Zhicheng Liu and Yu Lu and Wenhao Zhu and Zhichao Huang and Tao Li and Sitong Liu and Ningxin Peng and Shuaijie She and Lu Xu and Nuo Xu and Sen Yang and Runsheng Yu and Yiming Yu and Liehao Zou and Hang Li and Lu Lu and Yuxuan Wang and Yonghui Wu},
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  year={2025},
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+ eprint={2507.13618},
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  archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2507.13618},
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  }
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+ ```