Qwen3.5-4B-d0-vtok-lora-seeds

Qwen3.5-4B-d0-vtok-lora-seeds

Per-seed LoRA replicates for a documents-per-function suite: 50 synthetic constant functions, each answer a single added vocabulary token rather than a digit string.

Each model is trained on a corpus containing a fixed number of documents per function, with four runs per document count that are identical but for the order the documents were shuffled. They exist so the suite's results carry error bars over training order rather than resting on one trajectory.

Loading a run

from peft import PeftModel
from transformers import AutoModelForCausalLM

base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B")
model = PeftModel.from_pretrained(base, "Lamsheeper/Qwen3.5-4B-d0-vtok-lora-seeds", subfolder="10d_sd1001")

The base model needs the suite's added function tokens before an adapter will load against it; embed_tokens and lm_head are trained in full and ship inside each adapter.

Runs