opus-4b-dsl-step295-2026-05-01

LoRA adapter (rank 32) trained with RL on a custom Opus-Magnum-style motion-planning task using the dsl answer representation. Snapshot at training step 295 / 300.

Source training run

wandb: ls3ib3c4
tinker checkpoint: tinker://5b0405bf-15e8-585e-a12b-6e6aead9917f:train:0/sampler_weights/000295
distances: 1, 2, 3
task types: move, transmute (no bond)
learning rate: 1e-5
group size: 8, groups per batch: 16
renderer: qwen3_5_disable_thinking

Usage

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

base = "Qwen/Qwen3.5-4B"
adapter = "maxbittker/opus-4b-dsl-step295-2026-05-01"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)

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