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@@ -12,10 +12,12 @@ A lightly post-trained version of [talkie-lm/talkie-1930-13b-base](https://huggi
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  Recommended sampling settings are `temp=0.5, min_p=0.05, top_k=40, repetition_penalty=1.2, repetition_context_size=128`. Like the base model, it has a max context size of 2048. It additionally retians the (limited) few shot learning ability of the base model - going from 7.73% GSM8K at 1-shot to 11.30% at 2-shot to 12.36% at 4-shot.
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  ## Safety Disclaimer
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  This model is ancient and safety training is minimal. It may generate objectionable content, hateful content, or flat-up wrong content. Thus it is strictly for experimental purposes and I strongly recommend against its use in any user-facing application.
 
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  ## Chat template
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  This model uses a standard `user` / `assistant` chat API surface, but renders
 
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  Recommended sampling settings are `temp=0.5, min_p=0.05, top_k=40, repetition_penalty=1.2, repetition_context_size=128`. Like the base model, it has a max context size of 2048. It additionally retians the (limited) few shot learning ability of the base model - going from 7.73% GSM8K at 1-shot to 11.30% at 2-shot to 12.36% at 4-shot.
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+ The seed prompts used for initial persona elicitationcan be found [here](https://gist.github.com/N8python/00fda0195d4923908f6b1f0bd7337208) - each 'seed' was then continued by base talkie into a multi-turn conversation, the best of which formed the initial SFT round.
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  ## Safety Disclaimer
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  This model is ancient and safety training is minimal. It may generate objectionable content, hateful content, or flat-up wrong content. Thus it is strictly for experimental purposes and I strongly recommend against its use in any user-facing application.
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  ## Chat template
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  This model uses a standard `user` / `assistant` chat API surface, but renders