AIAny
Icon for item

Kimi K3 Coding & Debugging Agent Traces

Provides verified, model-attested end-to-end agent coding and debugging trajectories (JSONL). Each whole-session trace was produced by moonshotai/kimi-k3 on the pi/openrouter runtime, passed acceptance tests and independent model screening — useful for SFT, distillation, and analyzing tool-use behavior.

Introduction

Oops! Something went wrong

[next-mdx-remote-client] error compiling MDX: Unexpected character `1` (U+0031) before name, expected a character that can start a name, such as a letter, `$`, or `_` More information: https://mdxjs.com/docs/troubleshooting-mdx

Information

  • Websitehuggingface.co
  • Organizationsgreghavens, moonshiner, moonshotai, openrouter, Hugging Face
  • Authorsgreghavens
  • Published date2026/07/18

Categories

More Items

Evaluates whether video models reason according to physical laws by treating generated videos as visible reasoning traces and using a three-stage Perception–Formulation–Deduction protocol. Includes Orchard (400 mechanics videos), chain-of-frames prompting on annotated first frames, and a hybrid MLLM-plus-objective scoring suite for stage-resolved diagnostics.

Hugging Face

Provides intermediate pretraining checkpoints for the Aether-7B-5Attn base model to enable reproducible training-dynamics research. Includes three raw checkpoints (110k, 115k, 162k steps) packaged with model.safetensors, config, and tokenizer; uses a custom aether_v2_7way architecture requiring the aether_pkg loader.

Hugging Face

Provides 2,056 penetration-free cloth simulation trajectories (240 frames each, 493,440 frames, ~33 GB) across human garments, robotic manipulation, and object-collision scenarios. Includes per-vertex positions, per-frame displacements, mesh topology and collision fields under CC BY 4.0 — useful for training and evaluating learning-based cloth simulators.