Bu
Building LLM Gameplay Mechanics with Guidance
Building LLM Gameplay Mechanics with Guidance
I've written this article about how I'm using small LLMs and logit_bias to leverage the gameplay mechanics of my generative visual novels engine. I also open sourced the guidance library as an npm package.
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Launch Intel predictions
Analyze your own launch →86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
34%34% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
19%19% predicted probability of success on BetaList, based on ML models trained on real launch data.
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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