von3b

VON-3B

This is a hackathon submission repo and my 3B model. designed and ran the full path: SFT, RL, group-conditioned adaptive LoPD (rl & distillation method from my research), LoRA, weight edits, and the laptop GGUF pack.

VON-3B is one 3B model that covers two jobs: an offline coding assistant and an autonomous agent. after one public download it runs locally in llama.cpp or any inference engine on a standard 8 GB machine. no API key / network at inference.

we built it to:

• write and repair code
• keep reasoning short (base reasoned too long and took lots of time)
• emit a real one-line tool call (<tool_call>{...}</tool_call>) so it can act as an agent, not only a chatbot

other details:

• model card and weights: https://huggingface.co/josephmayo/von3b
• laptop artifact: von3b-Q8_0.gguf (llama.cpp, GGUF Q8_0, 3,285,475,488 bytes)
• runtime: llama.cpp only
• target machine: 4 vCPU, 8 GB RAM, integrated GPU, Ubuntu 22.04
• writeup: REPORT.md

we started from WeiboAI/VibeThinker-3B. On a matched EvalPlus 0.3.1 HumanEval check (same 164 tasks, greedy max_new=8192), the model beats that snapshot:

we report that comparison because we were compute-constrained - thats why we didnt run more evals. tool probe, 32 tasks, greedy max_new=256, same snapshot: the model emits a valid one-line <tool_call> with short think on 32 / 32. The base emits 0 / 32.

download:

bash download_model.sh
llama-cli -m model/von3b-Q8_0.gguf -c 65536 -ctk q4_0 -ctv q4_0 -ngl 0

ctx is 65,536 with Q4_0 K/V cache so the 8 GB profile can hold long coding sessions.

required package files (official template):

• metadata.json
• download_model.sh
• REPORT.md
• model/ (GGUF downloaded by the script, not committed)