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@@ -26,6 +26,9 @@ This repo contains the model checkpoints for:
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  - optimized with the loss <b>PPO</b>
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  - aligned using the SHP, Anthropic HH and Open Assistant datasets.
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  Please refer to our [code repository](https://github.com/ContextualAI/HALOs) or [blog](https://contextual.ai/better-cheaper-faster-llm-alignment-with-kto/) which contains intructions for training your own HALOs and links to our model cards.
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  If you find this repo or the technical paper useful in your research, please feel free to cite [our work](https://github.com/ContextualAI/HALOs/blob/main/assets/report.pdf):
 
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  - optimized with the loss <b>PPO</b>
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  - aligned using the SHP, Anthropic HH and Open Assistant datasets.
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+ To prompt archangel models, ensure that the format is consistent with that of TuluV2, i.e. `"<s>\n<|user|>\n" + <prompt> + "\n<|assistant|>\n</s>"`.
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+ Note that the BOS / EOS tokens should be excluded if automatically added by your tokenizer during batch collation.
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+
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  Please refer to our [code repository](https://github.com/ContextualAI/HALOs) or [blog](https://contextual.ai/better-cheaper-faster-llm-alignment-with-kto/) which contains intructions for training your own HALOs and links to our model cards.
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  If you find this repo or the technical paper useful in your research, please feel free to cite [our work](https://github.com/ContextualAI/HALOs/blob/main/assets/report.pdf):