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DaoyuanLi2816 merged 1 commit into from
Aug 13, 2026
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Prepare the v0.9.0 release #73

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5 changes: 4 additions & 1 deletion CHANGELOG.md
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Expand Up @@ -6,6 +6,8 @@ All notable changes to miniVERL are recorded here. The format follows

## [Unreleased]

## [0.9.0] - 2026-08-13

### Measured developer workload

- Published a checksummed RTX 4080 systems workload over 32 distinct consumed
Expand Down Expand Up @@ -930,7 +932,8 @@ Same-tokenizer only; one trajectory per forward pass; `swap` unavailable for
quantized models; only Qwen3 and Qwen2 architectures tested; single-seed GPU
results. The full list is in `docs/limitations.md`.

[Unreleased]: https://github.com/DaoyuanLi2816/mini-verl/compare/v0.8.1...HEAD
[Unreleased]: https://github.com/DaoyuanLi2816/mini-verl/compare/v0.9.0...HEAD
[0.9.0]: https://github.com/DaoyuanLi2816/mini-verl/compare/v0.8.1...v0.9.0
[0.8.1]: https://github.com/DaoyuanLi2816/mini-verl/compare/v0.8.0...v0.8.1
[0.8.0]: https://github.com/DaoyuanLi2816/mini-verl/compare/v0.7.1...v0.8.0
[0.7.1]: https://github.com/DaoyuanLi2816/mini-verl/compare/v0.7.0...v0.7.1
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4 changes: 2 additions & 2 deletions CITATION.cff
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Expand Up @@ -2,8 +2,8 @@ cff-version: 1.2.0
title: "miniVERL: A bounded single-GPU runtime for verl-style OPD"
message: "If you use miniVERL in your work, please cite it as below."
type: software
version: 0.8.1
date-released: 2026-08-12
version: 0.9.0
date-released: 2026-08-13
license: Apache-2.0
repository-code: "https://github.com/DaoyuanLi2816/mini-verl"
url: "https://github.com/DaoyuanLi2816/mini-verl"
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4 changes: 2 additions & 2 deletions PROJECT_STATE.md
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Expand Up @@ -4,9 +4,9 @@ Living build log for **miniVERL** (`mini-verl` / `miniverl` / CLI `miniverl`).
A checkbox is not evidence: every completed item names the command that was run
and what it printed.

Last updated: 2026-08-12.
Last updated: 2026-08-13.

Canonical release state: stable `v0.8.1` (`77a570721ec587e50f9b927b4c72a6fab8a73ca6`), development `0.9.0.dev0`.
Canonical release state: releasing `v0.9.0`.
Every public version claim is generated from `release-state.yaml` and gated by
`python scripts/release_state.py --check`.

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46 changes: 23 additions & 23 deletions PYPI.md
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@@ -1,5 +1,5 @@
<p align="center">
<img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/main/docs/banner.svg" alt="miniVERL — run verl-style OPD on one consumer GPU" width="880">
<img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.9.0/docs/banner.svg" alt="miniVERL — run verl-style OPD on one consumer GPU" width="880">
</p>

<div align="center">
Expand All @@ -8,15 +8,15 @@
[![Build](https://github.com/DaoyuanLi2816/mini-verl/actions/workflows/build.yml/badge.svg)](https://github.com/DaoyuanLi2816/mini-verl/actions/workflows/build.yml)
[![PyPI](https://img.shields.io/pypi/v/miniverl.svg)](https://pypi.org/project/miniverl/)
[![Python](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue)](https://www.python.org)
[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](https://github.com/DaoyuanLi2816/mini-verl/blob/main/LICENSE)
[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/LICENSE)

</div>

<p align="center">
<a href="https://pypi.org/project/miniverl/"><strong>PyPI</strong></a> ·
<a href="https://daoyuanli2816.github.io/mini-verl/"><strong>Stable docs</strong></a> ·
<a href="https://daoyuanli2816.github.io/mini-verl/dev/">Development docs</a> ·
<a href="https://github.com/DaoyuanLi2816/mini-verl/blob/main/README.zh-CN.md">中文</a>
<a href="https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/README.zh-CN.md">中文</a>
</p>

**Run a documented subset of verl-style on-policy distillation on one consumer
Expand All @@ -25,7 +25,7 @@ rollout → teacher scoring → actor update, records every local reinterpretati
and exports standard PEFT, Parquet and config artifacts for a pinned scale-out
handoff.

PyPI `v0.8.1` is stable; `main` is development. miniVERL is an independent
PyPI `v0.9.0` is stable; `main` is development. miniVERL is an independent
project with no upstream endorsement. It does not execute arbitrary verl YAML,
launch distributed jobs, or claim full algorithmic compatibility.

Expand All @@ -51,14 +51,14 @@ recipe and produce an inspectable PEFT adapter.

The `train` extra installs the ML runtime, but does not choose the correct CUDA
PyTorch wheel. The optional `cuda` extra adds bitsandbytes only. Follow the
[one-GPU installation and memory guide](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/single-gpu-guide.md) before a real
[one-GPU installation and memory guide](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/single-gpu-guide.md) before a real
run.

## Architecture

<picture>
<source media="(max-width: 640px)" srcset="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/main/docs/verl-local-runtime-mobile.svg">
<img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/main/docs/verl-local-runtime.svg" alt="verl-shaped YAML, overrides and Parquet prompts pass through a typed compiler; one CUDA GPU runs actor rollout, teacher scoring and actor update; inspectable artifacts can be handed to pinned verl while distributed execution remains outside miniVERL.">
<source media="(max-width: 640px)" srcset="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.9.0/docs/verl-local-runtime-mobile.svg">
<img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.9.0/docs/verl-local-runtime.svg" alt="verl-shaped YAML, overrides and Parquet prompts pass through a typed compiler; one CUDA GPU runs actor rollout, teacher scoring and actor update; inspectable artifacts can be handed to pinned verl while distributed execution remains outside miniVERL.">
</picture>

miniVERL uses one ordinary process and schedules model roles in phases. It does
Expand Down Expand Up @@ -113,13 +113,13 @@ miniverl plan --profile verl-opd-v0.8-single-gpu-v1 --config verl-opd.yaml \

External YAML must explicitly accept the high-risk local mappings printed by
`plan` before `run`; the packaged profile carries a value-bound reviewed
manifest. [Override precedence and safe input forms](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/config-overrides.md)
manifest. [Override precedence and safe input forms](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/config-overrides.md)
are documented without executing Hydra interpolation or shell text.

The public built-in profile deliberately uses upstream-shaped `name: vllm`
values. miniVERL classifies both rollout and teacher engine names as local
reinterpretations and executes them with sequential local HF phases; this is
not vLLM equivalence. See [For verl users](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/for-verl-users.md) for config,
not vLLM equivalence. See [For verl users](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/for-verl-users.md) for config,
data, role and error mappings.

## Tested profile boundary
Expand Down Expand Up @@ -149,8 +149,8 @@ with a 64-token response bound, and completed **8 current-policy updates** at
**3.1914 GiB peak reserved VRAM**. Median steady-state rollout, teacher-scoring
and update times were 9.7200, 0.4864 and 2.3260 seconds. A matched 4-update
interruption resumed to the same byte-identical trajectories, adapter and
optimizer tensors. See the [data-bound figure and full record](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/verl-opd-reference-workload.md);
the original one-update [pip smoke](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/opd-quickstart.md) remains preserved.
optimizer tensors. See the [data-bound figure and full record](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/verl-opd-reference-workload.md);
the original one-update [pip smoke](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/opd-quickstart.md) remains preserved.
A separate pinned SmolLM2-360M/1.7B compatibility smoke completed one full
rollout/scoring/update cycle; it is not a second measured recipe.

Expand All @@ -172,7 +172,7 @@ Automatic BF16/FP16 selection follows device support; it is not inferred from
marketing names such as 3070, 4080, 5090 or Titan. `miniverl doctor` reports the
installed CUDA/PyTorch path. Normal planning is weight-free; explicit
`plan --probe` adds bounded, cached CUDA measurements with zero optimizer
updates. See [hardware planning](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/hardware-planning.md). There is no
updates. See [hardware planning](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/hardware-planning.md). There is no
automatic downgrade to a different model,
teacher, context, top-k or loss when memory is tight.

Expand Down Expand Up @@ -200,30 +200,30 @@ The v0.8.1 export preserves student/teacher identities, Parquet bytes and pure
OPD overrides, but reports `launchable: false` until exact base snapshots are
materialized and validated against the installed pinned verl commit. Only then
does `bridge materialize` publish a checksummed `launch.sh`; distributed
execution remains untested. Review the [materialization contract](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/scaleout-materialization.md),
[bridge contract](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/verl-bridge.md) and [compatibility policy](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/compatibility.md).
execution remains untested. Review the [materialization contract](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/scaleout-materialization.md),
[bridge contract](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/verl-bridge.md) and [compatibility policy](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/compatibility.md).

The intended operating loop is **plan → inspect → run → inspect → export**.
`plan --out` byte-binds the YAML, ordered overrides and scanned Parquet inputs
to the exact native config; `run --plan` rejects drift before loading weights.
Its digest follows the run manifest, teacher cache and checkpoints. Direct
`run --config` remains available for experiments. See [immutable execution
plans](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/immutable-plans.md).
plans](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/immutable-plans.md).

## Research and validation

miniVERL keeps every measured study—including negative results, superseded
runs and preregistered early stops—public under the documentation. None is used
as a claim that OPD universally beats SFT, DPO or KD: see the
[v0.7 External Alignment Gate](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/alignment-external/alignment-external-v1.md),
[Alignment Lab](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/alignment-lab/alignment-lab-v1.md),
[RecoveryBench](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/recoverybench/recoverybench-v1.md), and the
[calculator study](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/benchmarking.md).
[v0.7 External Alignment Gate](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/alignment-external/alignment-external-v1.md),
[Alignment Lab](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/alignment-lab/alignment-lab-v1.md),
[RecoveryBench](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/recoverybench/recoverybench-v1.md), and the
[calculator study](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/benchmarking.md).

New runs establish tokenizer compatibility through structural identity. The
legacy behavioral fingerprint is retained only for migration and is not an
identity proof. Scientific caveats and immutable source hashes remain in the
detailed reports and [limitations](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/limitations.md).
detailed reports and [limitations](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/limitations.md).

## Development, security and license

Expand All @@ -236,6 +236,6 @@ pytest -q -m "not gpu and not network"

Contributions should keep the one-GPU boundary explicit and include tests for
new failure modes. Report vulnerabilities privately through
[SECURITY.md](https://github.com/DaoyuanLi2816/mini-verl/blob/main/SECURITY.md). See [CONTRIBUTING.md](https://github.com/DaoyuanLi2816/mini-verl/blob/main/CONTRIBUTING.md), the
[changelog](https://github.com/DaoyuanLi2816/mini-verl/blob/main/CHANGELOG.md), [citation metadata](https://github.com/DaoyuanLi2816/mini-verl/blob/main/CITATION.cff),
[reproducibility guide](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/reproducibility.md), and [Apache-2.0 license](https://github.com/DaoyuanLi2816/mini-verl/blob/main/LICENSE).
[SECURITY.md](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/SECURITY.md). See [CONTRIBUTING.md](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/CONTRIBUTING.md), the
[changelog](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/CHANGELOG.md), [citation metadata](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/CITATION.cff),
[reproducibility guide](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/docs/reproducibility.md), and [Apache-2.0 license](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.9.0/LICENSE).
2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -25,7 +25,7 @@ rollout → teacher scoring → actor update, records every local reinterpretati
and exports standard PEFT, Parquet and config artifacts for a pinned scale-out
handoff.

PyPI `v0.8.1` is stable; `main` is development. miniVERL is an independent
PyPI `v0.9.0` is stable; `main` is development. miniVERL is an independent
project with no upstream endorsement. It does not execute arbitrary verl YAML,
launch distributed jobs, or claim full algorithmic compatibility.

Expand Down
2 changes: 1 addition & 1 deletion README.zh-CN.md
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Expand Up @@ -23,7 +23,7 @@ verl 风格 YAML 与 Parquet prompt，在本地依次执行 actor rollout → te
actor update，记录每个本地语义重解释，并导出标准 PEFT、Parquet 与配置产物供固定版本
的 verl 接手扩展。

PyPI `v0.8.1` 是稳定版；`main` 是开发版。miniVERL 是独立项目，不代表上游背书；它
PyPI `v0.9.0` 是稳定版；`main` 是开发版。miniVERL 是独立项目，不代表上游背书；它
不执行任意 verl YAML、不启动分布式任务，也不声称完整的算法兼容性。

## 仅用 pip 的快速开始
Expand Down
45 changes: 19 additions & 26 deletions docs/generated/quality.json
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{
"schema_version": 2,
"release": "0.8.1",
"status": "released",
"quality_floor": "2,000+ tests and 85%+ branch coverage at v0.8.1",
"release": "0.9.0",
"status": "candidate",
"quality_floor": "2,000+ tests and 80%+ branch coverage at v0.9.0",
"local_validation": {
"scope": "the maintainer's workstation, where the GPU and Windows-specific paths actually run",
"commit": "ec0ffe9d8b75880487dde0d8ee022d82090c685f",
"commit_relationship": "exact product branch head; squash merge 8d3ebb2 carries the same tree and passed the full required CI matrix",
"measured_at": "2026-08-12T20:55:24-07:00",
"commit": "7a36f59d822d9d1393882c19ad4ef56b7364d43e",
"commit_relationship": "exact product branch head; merge fb78f64 carries the same tree and passed the full required CI matrix",
"measured_at": "2026-08-13T00:55:00-07:00",
"platform": "Windows 11",
"python": "CPython 3.10 for coverage; CPython 3.12 for CUDA",
"coverage_mode": "branch",
"cpu_non_gpu_non_network": {
"passed": 2178,
"skipped": 9,
"deselected": 21,
"branch_coverage_percent": 85.06,
"skip_reason": "six platform/privilege skips plus three pinned-verl conformance skips while the official package was intentionally absent from the general environment; the pinned profile ran separately in CI"
"passed": 2222,
"skipped": 10,
"deselected": 22,
"branch_coverage_percent": 83.95,
"skip_reason": "eight platform or privilege skips plus two pinned-verl conformance skips while the official package was intentionally absent from the general environment; all three pinned checks ran separately"
},
"gpu": {
"passed": 8,
Expand All @@ -27,23 +27,16 @@
}
},
"release_validation": {
"scope": "the exact immutable v0.8.1 release commit",
"commit": "77a570721ec587e50f9b927b4c72a6fab8a73ca6",
"scope": "the exact product merge, validated by CI before release metadata",
"commit": "fb78f64be411890f44a075ebac3cba2c5e1bec04",
"workflows": {
"ci": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31665123940",
"build": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31665123949",
"docs": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31665123951",
"pinned_verl_bridge": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31665123941",
"release": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31666095069"
"ci": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31680333897",
"build": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31680333905",
"docs": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31680333907",
"pinned_verl_bridge": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31680333928",
"release": "pending tag workflow"
},
"conclusion": "success",
"gpu_coverage": "none; no GPU runner is configured for this repository, so the GPU counts above exist only from the local measurement",
"publication": {
"pypi": "https://pypi.org/project/miniverl/0.8.1/",
"github_release": "https://github.com/DaoyuanLi2816/mini-verl/releases/tag/v0.8.1",
"wheel_sha256": "7c2a58f900cbab71689f7b229a46b5710b4aa2cbabc42af7526e2da04d9ba93e",
"sdist_sha256": "f4bf486b2427d1f37edc7b0afe0c4a4f17ad9da7fbd221b010d4c7d792698789",
"recovery_note": "OIDC publication succeeded; the tag workflow's final verifier retained two links intentionally removed from the product README, so the identical verified distributions were attached to the GitHub Release manually."
}
"gpu_coverage": "none; no GPU runner is configured for this repository, so the GPU counts above exist only from the local measurement"
}
}
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{% extends "base.html" %}

{% block announce %}
<div class="docs-channel" data-stable-version="0.8.1" data-dev-version="0.9.0.dev0">
<div class="docs-channel" data-stable-version="0.9.0" data-dev-version="0.9.0">
<strong id="docs-channel-label">Stable documentation</strong>
<label for="docs-version-selector">Version</label>
<select id="docs-version-selector" aria-label="Documentation version">
<option value="stable">Stable 0.8.1</option>
<option value="dev">Development 0.9.0.dev0</option>
<option value="stable">Stable 0.9.0</option>
<option value="dev">Development 0.9.0</option>
</select>
</div>
{% endblock %}
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