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@@ -26,8 +26,19 @@ This repo contains the model checkpoints for:
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  - optimized with the loss <b>SFT+KTO</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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  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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  - optimized with the loss <b>SFT+KTO</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.
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+ For example, a prompt should be formatted as follows, where `<|user|>` corresponds to the human's role and `<|assistant|>` corresponds to the LLM's role.
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+ The human should speak first:
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+ ```
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+ <|user|>
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+ Hi! I'm looking for a cake recipe.
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+ <|assistant|>
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+ What kind of cake?
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+ <|user|>
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+ Chocolate cake.
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+ <|assistant|>
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+ ```
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+ Note that a beginning-of-sequence (BOS) token is automatically added by all Archangel models during tokenization and does not have to be added by you. No end-of-sequence (EOS) token is added to the prompt.
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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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