ZuckLM

High-performance inference for Zuck-class workloads.

$ zuck ask "Fix this race condition."
give me the zuck

ZuckLM is an unofficial parody project built around one rigorously specified
task: giving you the Zuck. It is deliberately overengineered, locally runnable,
and honest about which part is a model and which part is a very committed bit.

Editions

Edition	What it is	Status
Oracle	Zero-parameter deterministic runtime with exact rare anomalies	Implemented
Prompted	Muse Glimmer behind an Ollama system prompt	Evaluated
Collapse	An MLX-VLM QLoRA behavior-collapse adapter	Trained and evaluated

Oracle is the reproducible joke. Prompted is the immediate 30B demo. Collapse
is the real lobotomy: a 105 MB reversible MLX adapter trained against a 30B
4-bit base.

The standardized Zuck apparatus

• ZuckLM Collapse: completed rank-4 MLX-VLM QLoRA adapter on Hugging Face.
• ZuckTrain: deterministic multilingual SFT generator, pinned recipe,
  LoRA-only freeze guard, sanitized training log, loss CSV, and loss curve.
• ZuckEval: exact adversarial and subject-family-held-out corpora with raw
  per-prompt outputs, timings, hashes, memory, and tool-call counts.
• ZuckBench: sober cross-edition compliance, latency, memory, and Zuck/s
  reporting with non-comparable units kept separate.
• ZuckLM Oracle: zero-parameter anomaly scheduler, CLI, OpenAI-shaped API,
  Ollama-shaped API, persistent crash-safe counter, and formal schedule spec.
• ZuckLM Prompted: the immediate Ollama demo and a useful control condition
  for comparing prompt compliance with actual weight modification.

The trained artifact is a com