8000 Advance development to 0.10.1.dev0 by DaoyuanLi2816 · Pull Request #84 · DaoyuanLi2816/mini-verl · GitHub
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5 changes: 3 additions & 2 deletions PROJECT_STATE.md
Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,12 @@ current product and evidence state rather than repeating release history.

Last updated: 2026-08-14.

Canonical release state: releasing `v0.10.0`.
Canonical release state: stable `v0.10.0` (`51264f86e8226b1abc6ca1901d379c5e6fabb81e`), development `0.10.1.dev0`.

## Release state

- Release candidate: `v0.10.0` (release commit pending).
- Stable: `v0.10.0` at `51264f86e8226b1abc6ca1901d379c5e6fabb81e`.
- Development: `0.10.1.dev0`.
- Stable docs: <https://daoyuanli2816.github.io/mini-verl/>.
- Development docs: <https://daoyuanli2816.github.io/mini-verl/dev/>.
- Historical build log: [v0.1-v0.9 archive](docs/history/project-state-v0.1-v0.9.md).
Expand Down
48 changes: 24 additions & 24 deletions PYPI.md
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@@ -1,5 +1,5 @@
<p align="center">
<img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.10.0/docs/banner.svg" alt="miniVERL — run verl-style OPD on one consumer GPU" width="880">
<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">
</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/v0.10.0/LICENSE)
[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](https://github.com/DaoyuanLi2816/mini-verl/blob/main/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/v0.10.0/README.zh-CN.md">中文</a>
<a href="https://github.com/DaoyuanLi2816/mini-verl/blob/main/README.zh-CN.md">中文</a>
</p>

**Run a documented subset of verl-style on-policy distillation on one consumer
Expand Down Expand Up @@ -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/v0.10.0/docs/single-gpu-guide.md) before a real
[one-GPU installation and memory guide](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/single-gpu-guide.md) before a real
run.

## Architecture

<picture>
<source media="(max-width: 640px)" srcset="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.10.0/docs/verl-local-runtime-mobile.svg">
<img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.10.0/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.">
<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.">
</picture>

miniVERL uses one ordinary process and schedules model roles in phases. It does
Expand Down Expand Up @@ -114,13 +114,13 @@ 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/v0.10.0/docs/config-overrides.md)
manifest. [Override precedence and safe input forms](https://github.com/DaoyuanLi2816/mini-verl/blob/main/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/v0.10.0/docs/for-verl-users.md) for config,
not vLLM equivalence. See [For verl users](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/for-verl-users.md) for config,
data, role and error mappings.

## Tested profile boundary
Expand Down Expand Up @@ -161,12 +161,12 @@ 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/v0.10.0/docs/verl-opd-reference-workload.md);
the original one-update [pip smoke](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/opd-quickstart.md) remains preserved.
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.
A separate pinned SmolLM2-360M/1.7B recipe consumed 32 distinct prompts across
8 updates at 1.4961 GiB peak reserved VRAM. Interruption/resume was
byte-identical, PEFT reload passed, and the exact-snapshot scale-out bundle
materialized successfully. See the [full SmolLM2 systems record](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/smollm2-opd-workload.md).
materialized successfully. See the [full SmolLM2 systems record](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/smollm2-opd-workload.md).

This is deliberately a runtime and artifact proof. It is not a throughput
benchmark, an alignment-quality endpoint, or evidence that OPD beats SFT, DPO
Expand All @@ -186,7 +186,7 @@ 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/v0.10.0/docs/hardware-planning.md). There is no
updates. See [hardware planning](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/hardware-planning.md). There is no
automatic downgrade to a different model,
teacher, context, top-k or loss when memory is tight.

Expand All @@ -198,7 +198,7 @@ miniverl hardware validate hardware-record.json
```

Community records remain unreviewed until their hashes and provenance pass the
[documented maintainer gate](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/community-benchmarks.md).
[documented maintainer gate](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/community-benchmarks.md).

## Data and artifact interoperability

Expand All @@ -224,30 +224,30 @@ The v0.9 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 [current scale-out contract](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/verl-opd-scaleout.md),
[legacy bridge](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/legacy-verl-bridge.md) and [compatibility policy](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/compatibility.md).
execution remains untested. Review the [current scale-out contract](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/verl-opd-scaleout.md),
[legacy bridge](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/legacy-verl-bridge.md) and [compatibility policy](https://github.com/DaoyuanLi2816/mini-verl/blob/main/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/v0.10.0/docs/immutable-plans.md).
plans](https://github.com/DaoyuanLi2816/mini-verl/blob/main/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/v0.10.0/docs/alignment-external/alignment-external-v1.md),
[Alignment Lab](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/alignment-lab/alignment-lab-v1.md),
[RecoveryBench](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/recoverybench/recoverybench-v1.md), and the
[calculator study](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/benchmarking.md).
[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).

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/v0.10.0/docs/limitations.md).
detailed reports and [limitations](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/limitations.md).

## Development, security and license

Expand All @@ -260,6 +260,6 @@ 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/v0.10.0/SECURITY.md). See [CONTRIBUTING.md](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/CONTRIBUTING.md), the
[changelog](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/CHANGELOG.md), [citation metadata](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/CITATION.cff),
[reproducibility guide](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/docs/reproducibility.md), and [Apache-2.0 license](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.10.0/LICENSE).
[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).
25 changes: 19 additions & 6 deletions docs/generated/quality.json
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@@ -1,15 +1,15 @@
{
"schema_version": 2,
"release": "0.10.0",
"status": "candidate",
"status": "released",
"quality_floor": "2,000+ tests and 80%+ branch coverage at v0.10.0",
"local_validation": {
"scope": "the maintainer's workstation, where the GPU and Windows-specific paths actually run",
"commit": "b2157301e5d0fd5652d8a1bd02fbf5e87735f9d3",
"commit_relationship": "final product head before release-only metadata; merge 0749e58 carries the same tree and passed the full required CI matrix",
"measured_at": "2026-08-14T01:32:04-07:00",
"platform": "Windows 11",
"python": "CPython 3.10 for coverage, local CUDA and network tests",
"python": "CPython 3.10 for coverage, local CUDA/network tests and the clean public CUDA install",
"coverage_mode": "branch",
"cpu_non_gpu_non_network": {
"passed": 2300,
Expand All @@ -28,10 +28,23 @@
},
"release_validation": {
"scope": "the exact immutable v0.10.0 release commit",
"commit": "pending",
"workflows": {},
"conclusion": "pending",
"commit": "51264f86e8226b1abc6ca1901d379c5e6fabb81e",
"workflows": {
"ci": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31784912998",
"build": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31785370631",
"docs": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31785370654",
"pinned_verl_bridge": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31785370709",
"release": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31785370545"
},
"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": null
"publication": {
"pypi": "https://pypi.org/project/miniverl/0.10.0/",
"github_release": "https://github.com/DaoyuanLi2816/mini-verl/releases/tag/v0.10.0",
"documentation": "https://daoyuanli2816.github.io/mini-verl/",
"immutable_documentation_build": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31785370654",
"wheel_sha256": "ff6bff4169dc5076fb6f3b10c2e38003dd681fb6513b1a0e3719948af16cc560",
"sdist_sha256": "13eab0de5f339e125a5a9c2cab707efeee28cc32cbe0f35030943ba0eef01ae2"
}
}
}
4 changes: 2 additions & 2 deletions docs/overrides/main.html
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@@ -1,12 +1,12 @@
{% extends "base.html" %}

{% block announce %}
<div class="docs-channel" data-stable-version="0.10.0" data-dev-version="0.10.0">
<div class="docs-channel" data-stable-version="0.10.0" data-dev-version="0.10.1.dev0">
<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 0.10.0</option>
<option value="dev">Development 0.10.0</option>
<option value="dev">Development 0.10.1.dev0</option>
</select>
</div>
{% endblock %}
22 changes: 22 additions & 0 deletions docs/release-checklist.md
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Expand Up @@ -4,6 +4,11 @@ This is the release gate and publication record for miniVERL. A checked item
names an invariant exercised on the stated source. Publication begins only
after the exact release commit and its remote checks are green.

## v0.10.1 development

- [x] Begin from the verified v0.10.0 release and advance only the canonical
development state to `0.10.1.dev0`.

## v0.10.0 development

- [x] Begin from the verified v0.9.1 release and `0.10.0.dev0` canonical state.
Expand Down Expand Up @@ -220,6 +225,23 @@ unauthorized after checkpoint-selection failure**.

## After the tag

- [x] v0.10.0 release run
[`31785370545`](https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31785370545)
completed the full release gate, OIDC Trusted Publishing, per-file
attestations, exact public install and GitHub Release creation for commit
`51264f86e8226b1abc6ca1901d379c5e6fabb81e`.
- [x] PyPI and the
[v0.10.0 GitHub Release](https://github.com/DaoyuanLi2816/mini-verl/releases/tag/v0.10.0)
expose identical files: wheel SHA-256
`ff6bff4169dc5076fb6f3b10c2e38003dd681fb6513b1a0e3719948af16cc560`,
sdist SHA-256
`13eab0de5f339e125a5a9c2cab707efeee28cc32cbe0f35030943ba0eef01ae2`.
- [x] A fresh CPython 3.10 environment installed CUDA PyTorch 2.13.0+cu130 and
public `miniverl[train,cuda]==0.10.0`; `doctor` reported RTX 4080 CUDA,
BF16, GPU training and QLoRA capabilities available.
- [x] Advance subsequent development to `0.10.1.dev0`; the main-only docs
deployment is verified after this state-sync PR merges.

- [x] v0.9.1 release run
[`31772945981`](https://github.com/DaoyuanLi2816/mini-verl/actions/runs/31772945981)
completed the full release gate, OIDC Trusted Publishing, per-file
Expand Down
6 changes: 3 additions & 3 deletions release-state.yaml
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Expand Up @@ -17,13 +17,13 @@
# such distinction, which is how its tag shipped a docs selector still
# advertising "Stable 0.6.1 / Development 0.6.2.dev0".
schema_version: 1
phase: release
phase: development

stable:
version: "0.10.0"
tag: "v0.10.0"
release_commit: "pending"
release_commit: "51264f86e8226b1abc6ca1901d379c5e6fabb81e"
released_at: "2026-08-14"

development:
version: "0.10.0"
version: "0.10.1.dev0"
2 changes: 1 addition & 1 deletion src/miniverl/__init__.py
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Expand Up @@ -14,6 +14,6 @@

from __future__ import annotations

__version__ = "0.10.0"
__version__ = "0.10.1.dev0"

__all__ = ["__version__"]
0