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Shiki42/ctr-place-dual-shoes-original-20260919

published by @Shiki42

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
159
Last 30 days
120
Likes
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Size
109.5 MB
Created on HF
2026-09-19
Age
1 months ago

Description

⚠️ PENDING · INCOMPLETE 49/50 · NOT FOR USE

This public repository preserves diagnostic evidence from CTR Experiment E350.

It is intentionally published despite being incomplete and is not a usable

training, evaluation, or benchmark dataset.

Do not use it for:

model training or fine-tuning;

model evaluation;

benchmark or result comparison;

claims of complete Original coverage.

Why it is incomplete

The fixed Place Dual Shoes cohort contains 50 scene seeds.… See the full description on the dataset page: https://huggingface.co/datasets/Shiki42/ctr-place-dual-shoes-original-20260919.

Tags

task_categories:roboticsregion:uslerobotrobotwinincompletediagnostic-evidence

README current version from Hugging Face

pretty_name: "CTR Place Dual Shoes Original — INCOMPLETE / NOT FOR USE"
task_categories:

  • robotics
    tags:
  • lerobot
  • robotwin
  • incomplete
  • diagnostic-evidence

⚠️ PENDING · INCOMPLETE 49/50 · NOT FOR USE

This public repository preserves diagnostic evidence from CTR Experiment E350.
It is intentionally published despite being incomplete and is not a usable
training, evaluation, or benchmark dataset.

Do not use it for:

  • model training or fine-tuning;
  • model evaluation;
  • benchmark or result comparison;
  • claims of complete Original coverage.

Why it is incomplete

The fixed Place Dual Shoes cohort contains 50 scene seeds. Official native
RoboTwin expert collection succeeded for 49 scenes. Fixed scene seed 73
(slot 29) did not satisfy the unchanged official task success criterion after
multiple planner-seed-only retries. Collection was stopped by explicit user
request during E350-R006; the failed scene was not replaced.

Published status: PENDING_INCOMPLETE_NOT_FOR_USE.

What is included

  • 49 successful fixed-scene episodes in LeRobot v3 format;
  • official native expert semantics without retiming;
  • centered_fovy90 wrist cameras with verified recorded intrinsics and mounts;
  • measured state at t aligned to command target at t+1;
  • IdleMask disabled and no IdleMask columns;
  • exact global per-feature quantile metadata computed only over the 49 accepted
    episodes;
  • source-scene lineage, collection summary, revision marker, and SHA-256 manifest.

The quantile metadata is included for provenance only and does not authorize
training or imply that this incomplete distribution is valid normalization data.

Provenance and lifecycle

  • Experiment: E350
  • Task: RoboTwin place_dual_shoes
  • Intended fixed scenes: 50
  • Published successful scenes: 49
  • Missing seed: 73
  • Dataset lifecycle: reported / Pending; not archived or confirmed
  • Publication purpose: diagnostic evidence preservation only

See .ctr-revision.json, meta/original_definition.json,
meta/collection_summary.json, meta/original_manifest.json, and
SHA256SUMS for machine-readable identity and warnings.

README history 4 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.

  1. 2026-09-19Add artifact cardbf5da002.1 KB
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  2. 2026-09-19Add verified SHA-256 artifact manifest36758400 B
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  3. 2026-09-19Add files using upload-large-folder tool24ce3d60 B
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  4. 2026-09-19initial commit42200dd0 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

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Download the dataset

0

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("Shiki42/ctr-place-dual-shoes-original-20260919")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Shiki42/ctr-place-dual-shoes-original-20260919", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/Shiki42/ctr-place-dual-shoes-original-20260919
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