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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - stanfordnlp/SHP
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+ - Anthropic/hh-rlhf
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+ - OpenAssistant/oasst1
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ tags:
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+ - human feedback
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+ - rlhf
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+ - preferences
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+ - alignment
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+ - HALO
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+ - halos
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+ - dpo
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+ - rl
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+ ---
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+
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+ ![halos](https://gist.github.com/assets/29318529/fe2d8391-dbd1-4b7e-9dc4-7cb97e55bc06)
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+
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+ This repo contains the model checkpoints for:
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+ - model family <b>pythia2-8b</b>
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+ - optimized with the loss <b>SFT+SLIC</b>
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+ - aligned using the SHP, Anthropic HH and Open Assistant datasets.
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+
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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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+
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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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+
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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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+ ```
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+ @techreport{ethayarajh2023halos,
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+ author = {Ethayarajh, Kawin and Xu, Winnie, and Jurafsky, Dan and Kiela, Douwe},
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+ title = {Human-Centered Loss Functions (HALOs)},
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+ institution = {Contextual AI},
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+ note = {https://github.com/ContextualAI/HALOs/blob/main/assets/report.pdf},
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+ year = {2023},
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+ }
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+ ```