uno-qwen3-8B

<h1 align="center"><strong>Uno Qwen3-8B</strong></h1>

Paper: Unlocking Lossless Speedups in LLMs via Discrete Diffusion
Project page: https://s-sahoo.github.io/uno/

This repository is a self-contained inference bundle for Uno-Qwen3-8B. The frozen verifier/base checkpoint is stored at the repository root, and the rank-128 gated LoRA adapter used for noisy draft rows is stored under adapter/.

Uno applies the adapter selectively during draft-noise forwards. Seed, prefill, verification, and autoregressive rows use the frozen base weights. Loading the adapter as an ordinary always-on PEFT adapter does not reproduce Uno decoding.

Repository layout

s-sahoo/uno-qwen3-8B
|-- config.json
|-- model-*.safetensors
|-- model.safetensors.index.json
|-- modeling_sdar.py
|-- tokenizer files
`-- adapter/
    |-- adapter_config.json
    `-- adapter_model.safetensors

Evaluation protocol

The reproducible entry points are the Qwen benchmark wrappers in ifm-ai/uno. Unless an experiment explicitly overrides a setting, the release wrappers use the following protocol:

Math tasks use the instruction Please reason step by step and put your final answer in \boxed{}.. Benchmarks that request it in the release configuration use reasoning_effort=high through the chat template.

Generation artifacts are written to generations.jsonl. generation_summary.json records all resolved settings, aggregate output TPS, and TPF as accepted tokens divided by decoder sequence-forwards. Accuracy and grader details are written to grades.jsonl and scores.json when the selected benchmark has a local grader.

from huggingface_hub import snapshot_download

snapshot = snapshot_download(
    "s-sahoo/uno-qwen3-8B",
    revision="<pinned-commit-sha>",
)
print("Base:", snapshot)
print("Adapter:", f"{snapshot}/adapter")

With the Uno repository:

UNO_BUNDLE_REPO=s-sahoo/uno-qwen3-8B \
UNO_BUNDLE_REVISION=<pinned-commit-sha> \
  bash scripts/qwen/run_gsm8k_eval.sh

The repository contains custom model code. Conventional Transformers loading of the base checkpoint requires trust_remote_code=True. Official Uno generation additionally requires conditional adapter routing and lossless verification implemented by the Uno runtime.