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## Contact
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E-Mail: [Zhilin Wang](mailto:zhilinw@nvidia.com)
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## Citation
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If you find this model useful, please cite the following works
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## References(s):
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* [HelpSteer2-Preference](https://arxiv.org/abs/2410.01257)
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* [SteerLM method](https://arxiv.org/abs/2310.05344)
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* [HelpSteer](https://arxiv.org/abs/2311.09528)
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* [HelpSteer2](https://arxiv.org/abs/2406.08673)
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* [Introducing Llama 3.1: Our most capable models to date](https://ai.meta.com/blog/meta-llama-3-1/)
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* [Meta's Llama 3.1 Webpage](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1)
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* [Meta's Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)
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## Model Architecture:
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**Architecture Type:** Transformer <br>
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# Training & Evaluation:
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## Datasets:
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**Data Collection Method by dataset** <br>
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## Citation
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If you find this model useful, please cite the following works
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## References(s):
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* [NeMo Aligner](https://arxiv.org/abs/2405.01481)
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* [HelpSteer2-Preference](https://arxiv.org/abs/2410.01257)
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* [HelpSteer2](https://arxiv.org/abs/2406.08673)
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* [Introducing Llama 3.1: Our most capable models to date](https://ai.meta.com/blog/meta-llama-3-1/)
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* [Meta's Llama 3.1 Webpage](https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_1)
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* [Meta's Llama 3.1 Model Card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md)
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## Model Architecture:
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**Architecture Type:** Transformer <br>
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# Training & Evaluation:
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## Alignment methodology
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* REINFORCE implemented in NeMo Aligner
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## Datasets:
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**Data Collection Method by dataset** <br>
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