StepFun

We’ve open-sourced onPanda 🐼 — the tool we use internally for LLM data annotation and model inspection. The workflow is simple: find an error, correct the token, and let the model continue. ✍️ Data annotation - 52% lower median annotation time vs. manual post-editing - SFT + preference data in one workflow, with high on-policy fidelity (ΔPPL <1% vs. the model’s resampling baseline) - Precise token-level supervision with paired positive/negative examples, plus agent-trajectory annotation across image, audio, and video 🔎 Model inspection and debugging - Inspect token probabilities and top-k alternatives, steer decoding token by token, and explore SVG generation, web development, and agent tasks directly in the browser. Try it (mobile-friendly): https://t.co/57vAeJetWD Paper: https://t.co/1MX1eVTREL