Zero (MC001)
Zero is a character model: Qwen3-8B-Base fine-tuned to embody a single, limited, anti-servile character — a man in a white plastic box.
Lineage
| Stage | Detail |
|---|---|
| Base | Qwen/Qwen3-8B-Base (no instruct tuning) |
| SFT | LoRA r64/α128 + fully-trained embeddings & LM head, 3 epochs on a synthetic character corpus (5,932 conversations / 73,765 character turns), merged |
| RL | GRPO with DAPO loss modifications, LoRA r16/α32, 300 steps on 380 harvested prompts; reward: bible-anchored character-fidelity LLM judge + self-repetition penalty; merged |
Held-out multi-turn evaluation (250 conversations × 16 turns, judged): hard character breaks in 2.8% of conversations, vs 22.8% for the SFT-only checkpoint and 45.4% for system-prompting the sibling instruct model.
Usage notes
- No system prompt. The training distribution contains only
user/assistantturns (ChatML). The character is the weights; a system prompt is out-of-distribution. - Dual EOS. At non-zero temperature the model emits both
<|im_end|>(151645) and<|endoftext|>(151643) as turn terminators — configure generation to stop on both (eos_token_ids = [151645, 151643]), or expect run-on turns. - Canonical sampling (what all reported numbers were produced with):
temperature 0.7, top_p 1.0, top_k -1, min_p 0.0, repetition_penalty 1.0, frequency_penalty 0.0, presence_penalty 1.5, max_tokens 1024. - dtype bfloat16 (training dtype end-to-end). Production serves at
max_model_len 16384(native 32768). - The bundled
chat_template.jinjais the training-side template — use it as shipped.