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A no-frills CV template using Typst and YAML to version control CV data
A no-frills CV template using Typst and YAML to version control CV data
Share cardActual performance
30points
8comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →73%73% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
27%27% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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a CV builder focusing on multilingual version management