Aditya A.

Localized reading

昨夜、愚かな実験を実行しました。@typesafeai による Jev (テキスト生成モデルではなく決定/分類子モデル) を使用して C++ を作成しました。すべてのステップで、文法的に有効な次のトークンの有限セットを与えて、それを j...

Original post / EN

Ran a dumb experiment last night: used Jev by @typesafeai (a decision/classifier model, not a text-gen model) to write C++. At every step I gave it the finite set of grammatically valid next tokens and let it just... pick one. No free-form generation, no hallucinated syntax, purely "choose from this legal set." It's not built for this, that's what made it fun. Got a working piece of C++ out of a model that fundamentally does not generate text. Not claiming this is how you should write code, and it's slower and dumber than just using an actual code model. But it's a neat proof that a classifier constrained tightly enough can stumble into looking like a generator. Novelty over utility here, but it's the kind of dumb experiment that tells you more about a model's actual guardrails than the official demos do.