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ZuckLM
A deliberately overengineered parody that 'gives you the Zuck', with a deterministic Oracle edition, a prompted Muse Glimmer edition and an MLX QLoRA fine-tune of Muse Glimmer 30B for Apple Silicon.
# ZuckLM [](https://github.com/brenden7158/zucklm/actions/workflows/ci.yml) [](https://huggingface.co/brenden7158/ZuckLM-Muse-Glimmer-30B-MLX-LoRA) [](https://huggingface.co/datasets/brenden7158/ZuckLM-Collapse-SFT-v2) [](LICENSE)   > High-performance inference for Zuck-class workloads. ```console $ 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






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