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Upload step-150 LoRA adapter from opus-4b-dsl-mixed run
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metadata
base_model: Qwen/Qwen3.5-4B
library_name: peft
tags:
  - tinker
  - peft
  - lora
  - opus-magnum

opus-4b-dsl-mixed-step150-2026-04-29

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 150 / 300.

Source training run

  • wandb: opus-4b-dsl-mixed-2026-04-29 (mqhz79iy)
  • tinker checkpoint: tinker://addea7a1-fbe5-59b8-a467-5de3736c3404:train:0/sampler_weights/000150
  • distances: 1, 2, 3, 4
  • task types: move, transmute, bond
  • hard_task_fraction: 0.15 (cap on bond + d=4 share of train pool)
  • 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-mixed-step150-2026-04-29"
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, adapter)