Rewnozom-GGUF

Rewnozom-GGUF

GGUF conversion of Rewnozom/Rewnozom, derived from Qwen/Qwen2.5-7B-Instruct-1M.

• Original model: Rewnozom/Rewnozom
• Converted model: Rewnozom/Rewnozom-GGUF
• Format: GGUF
• Runtime targets: llama.cpp, Ollama, LM Studio, Jan, and other GGUF loaders

Personal recommendation: start with the two hybrid MX profiles, MX-k_quants and MX-legacy-quants, because they keep the sensitive tensors higher while leaving the rest on a compact base quant.

Available Quantizations

Only quantizations with an actual .gguf file in this workspace are listed.

Quantization Groups

Recommended Starting Points

Actual quality and speed depend on runtime, CPU/GPU offload, context length, and prompt workload. Validate the target quant against your real tasks before using it as a default.

llama.cpp

Run directly from a local GGUF file:

llama-cli -m k_quants/Q4_K_M/Rewnozom-1M-LR.Q4_K_M.gguf \
  -p "Review this implementation plan for missing constraints."

Start an OpenAI-compatible local server:

llama-server -m k_quants/Q4_K_M/Rewnozom-1M-LR.Q4_K_M.gguf

Dataset Context

The model is associated with a synthetic reasoning/control-plane dataset family covering:

• boolean CSP logic
• branch-dependent task DAGs
• ordering and plan repair
• multi-hop forward inference
• request decomposition
• context relevance
• deterministic state transitions
• memory lifecycle
• retrieval/navigation policy
• executor routing
• tool execution
• permissions
• multi-agent orchestration
• result validation
• retry/escalation
• composite execution kernel behavior

The dataset design uses deterministic formal worlds, double oracle checks, structural dedupe, and machine-verifiable answers rather than synthetic prose chain-of-thought.

Limitations

• GGUF quantization changes numerical behavior compared with the source model.
• Lower-bit quants trade quality for memory and speed.
• Permission enforcement, destructive actions, and state mutation should remain controlled by deterministic application logic.

Attribution

This conversion is based on Rewnozom/Rewnozom, which is derived from Qwen/Qwen2.5-7B-Instruct-1M and follows the Apache 2.0 license.

page:

Base model: https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M

Rewnozom/Rewnozom: https://huggingface.co/Rewnozom/Rewnozom

Rewnozom/Rewnozom-GGUF: https://huggingface.co/Rewnozom/Rewnozom-GGUF

Ollama: https://ollama.com/tobraa92/Rewnozom

Portfolio: https://tobiasraanaes.se/