A runnable inference procedure, using unchanged IBM Granite 4.0–1B weights and TypeSafe's hosted Jev verifier. This release implements the current There are no newly trained weights, adapters, internal routing changes or Jev weights in this package. It is a custom serial Python runner, not an AutoModel checkpoint, hosted Hugging Face chat widget or vLLM plugin. The earlier trained-proposal artifact is a different preserved experiment. 1. Frozen Granite generates one greedy answer. 2. The same weights generate one independent sample (temperature 0.7, top-p 0.95, top-k 50), with a separate cache and a reproducible input-specific seed. 3. Exactly equal texts keep the native answer without…
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