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Arushhh/phase2-drafter-swap

published by @Arushhh

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
184
Last 30 days
184
Likes
-
Size
19.5 GB
Created on HF
2026-10-05
Age
16 days ago

Description

Phase 2 drafter swap (no expert pool): code, results, data, weights in one place

Frozen SDAR-30B-A3B-Chat-b32 + the Phase 1 LoRA judge (128M-token corpus, weights hash 35805974), no expert pool,

nothing trained. Only the drafter changes: SDAR-1.7B (reference, Phase 1) vs CoDA-1.7B (F2_nopool) vs

Qwen3-0.6B diffusion (S1_nopool), on HumanEval 164, MBPP 257, GSM8K-500, IFEval-541, MATH-500, GPQA-D 198, AIME 90.

Get everything with one command

Tested 2026-10-05 from… See the full description on the dataset page: https://huggingface.co/datasets/Arushhh/phase2-drafter-swap.

Tags

region:us

README current version from Hugging Face

Phase 2 drafter swap (no expert pool): code, results, data, weights in one place

Frozen SDAR-30B-A3B-Chat-b32 + the Phase 1 LoRA judge (128M-token corpus, weights hash 35805974), no expert pool,
nothing trained. Only the drafter changes: SDAR-1.7B (reference, Phase 1) vs CoDA-1.7B (F2_nopool) vs
Qwen3-0.6B diffusion (S1_nopool), on HumanEval 164, MBPP 257, GSM8K-500, IFEval-541, MATH-500, GPQA-D 198, AIME 90.

Get everything with one command

Tested 2026-10-05 from a clean environment without a token: 2,217 files, ~21 GB, about 7 min.

pip install -U huggingface_hub          # provides the `hf` command (huggingface-cli was removed in huggingface_hub 1.x)
hf download Arushhh/phase2-drafter-swap --repo-type dataset --local-dir phase2_bundle    # all ~21 GB; no token needed (public)

Layout

path what
assets/results/TABLES.md, metrics.json every comparison table: accuracy, Δ vs SDAR-1.7B with 95% CI, experts/token, MoE-only / full-pipeline / drafter-only speedups, passes/block, draft tokens kept
phase2/analysis/nopool/ the analysis: REPORT.md (dip? why? scope), IMPROVEMENT_PLAN.md, analysis.json, figures, scripts
phase2/decode/F2_nopool/<set>/, phase2/decode/S1_nopool/<set>/ per-item records (*.jsonl), running metrics (*.running.jsonl), and experts.tar / judge.tar / traces.tar (per-forward expert bitmasks + router top-8, every judge read's probabilities, drafter confidences)
phase2/plots/ all plots (also on W&B arushsharma536-spe-iit/phase2-drafter-swap)
phase2/jobs/, phase2/*.log, phase2/setup/ job logs, launcher logs, environment freezes, setup checks
assets/judge_128M_tok_000128000000/ the judge LoRA weights used (from Arushhh/c1b-judge-lora-sdar30b-b32)
assets/ref_S0_SDAR1.7B_judge128M_nopool/<set>/ reference A: SDAR-1.7B + judge, no pool (Phase 1 records)
assets/ref_stock_30B/ reference B: stock 30B decode records
assets/datasets/ IFEval-541 (frozen, + sha256) and the manifest of the other benchmark datasets (public HF datasets)
code/*.tar.gz the code at the commit that produced this (git archive); also on GitHub NoviceCoderInfinity/diffusion-moe-general-expert branch phase2-drafter-swap

Not part of the results: phase2/decode/F2/, phase2/jobs/decode_F2* (non-nopool) and phase2/analysis/logprob/ are an
earlier run with the DES48 expert pool that was stopped at the user's request; ignore them.

Replicate on a new 8-GPU box

Unpack the code tarball (or clone the branch), put HF_TOKEN in .env, then
bash code/phase2/replicate_nopool.sh (see docs/PHASE2_NOPOOL_REPLICATE.md).

Models and drafters are public at pinned revisions: JetLM/SDAR-30B-A3B-Chat-b32 @ c351bbc, JetLM/SDAR-1.7B-Chat-b32 @ 2c83c05,
Salesforce/CoDA-v0-Instruct @ f2d40ce, dllm-hub/Qwen3-0.6B-diffusion-bd3lm-v0.1 @ 60f77bb.

README history 20 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("Arushhh/phase2-drafter-swap")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Arushhh/phase2-drafter-swap", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/Arushhh/phase2-drafter-swap
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