| --- |
| pretty_name: V-JEPA Reproduce Recipe |
| license: other |
| license_name: mixed-upstream-terms |
| license_link: https://huggingface.co/datasets/BootsofLagrangian/V-JEPA-Reproduce-Recipe/blob/main/README.md#license-and-access |
| tags: |
| - video |
| - metadata |
| - pretraining |
| - v-jepa |
| - deduplication |
| configs: |
| - config_name: samples |
| data_files: |
| - split: train |
| path: "samples/**/*.parquet" |
| default: true |
| - config_name: assets |
| data_files: |
| - split: train |
| path: "assets/**/*.parquet" |
| - config_name: memberships |
| data_files: |
| - split: train |
| path: "memberships/**/*.parquet" |
| - config_name: dataset_roles |
| data_files: |
| - split: train |
| path: "dataset_roles.parquet" |
| - config_name: dataset_stats |
| data_files: |
| - split: train |
| path: "dataset_stats.parquet" |
| - config_name: source_coverage |
| data_files: |
| - split: train |
| path: "source_coverage.parquet" |
| --- |
| |
| # V-JEPA Reproduce Recipe |
|
|
| Private, metadata-only planning surface for reconstructing a large-scale |
| V-JEPA-style observation-pretraining mixture. This repository does **not** |
| redistribute source videos and does not grant rights beyond each upstream |
| dataset's terms. |
|
|
| ## Current release |
|
|
| - Manifest ID: `YTWS-CANONICAL-MANIFEST-V1` |
| - Run ID: `823483f781094a668cf6682828723d16` |
| - Schema version: `1` |
| - Source memberships: `485,265,004` |
| - Exact interval samples: `469,907,459` |
| - Canonical assets: `82,701,705` |
| - Parquet shards: `3,292` |
| - Parquet-only payload: `41,557,148,598` bytes (38.70 GiB) |
|
|
| The manifest combines the 11 currently materialized metadata sources: COIN, |
| DROID, EPIC-KITCHENS-100, HD-VILA-100M, HowTo100M ID recovery (unattested ID |
| mirror), InternVid, Kinetics-710, OpenVid-1M, Panda-70M, YouNiverse (structural |
| HF mirror), and YT-Temporal-180M (unverified mirror). Provenance quality is |
| recorded per source. Dataset membership is not a statement that every media URL |
| remains reachable. |
|
|
| ## Layout |
|
|
| ```text |
| manifest.json |
| samples/dedup_bucket=00..ff/*.parquet |
| assets/dedup_bucket=00..ff/*.parquet |
| memberships/dataset_id=<name>/dedup_bucket=00..ff/*.parquet |
| dataset_roles.parquet |
| dataset_stats.parquet |
| source_coverage.parquet |
| ``` |
|
|
| - `samples`: exact `(platform, video_id, millisecond interval)` identities. |
| - `assets`: source video or trajectory identities without interval duplication. |
| - `memberships`: lossless lineage back to each source metadata row. |
| - `dataset_roles`: the overlapping `broad_in_the_wild`, `instructional`, |
| `curated_temporal_action`, `ego_and_synchronized_observation`, and |
| `hosted_quality_video` views. |
| - `dataset_stats`: per-source row, dedup, reservation, and resolvability counts. |
| - `source_coverage`: included and excluded catalog sources with provenance or |
| exclusion reasons. |
|
|
| Captions, action labels, and other source-specific payload tables are not part |
| of this repository. Membership rows retain `dataset_id`, `source_row_id`, and |
| `metadata_revision` as lineage keys for consumers that separately acquired the |
| corresponding upstream payload. The HowTo100M recovery contains IDs only; the |
| canonical captions/tasks archive was unavailable and cannot be reconstructed |
| from this release. |
|
|
| ## Load with Hugging Face Datasets |
|
|
| Authentication is required because the repository is private; export a token |
| with read access as `HF_TOKEN`. The repository exposes six named |
| configurations. `samples` is the default, so both the bare call and an explicit |
| `"samples"` select the deduplicated interval table. Use `"assets"` and |
| `"memberships"` for the other large tables; `"dataset_roles"`, |
| `"dataset_stats"`, and `"source_coverage"` expose the three compact indexes. |
|
|
| The simplest streaming load is: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| repo_id = "BootsofLagrangian/V-JEPA-Reproduce-Recipe" |
| samples = load_dataset(repo_id, "samples", split="train", streaming=True) |
| |
| web_train = samples.filter( |
| lambda row: ( |
| "broad_in_the_wild" in row["roles"] |
| and not row["is_reserved"] |
| and row["directly_resolvable"] |
| ) |
| ) |
| ``` |
|
|
| For source lineage, load the `memberships` configuration and filter by |
| `dataset_id`. To minimize shard discovery and assign the 256 hash buckets |
| directly across workers, address only the required source and bucket paths: |
|
|
| ```python |
| dataset_id = "howto100m" |
| bucket = "00" |
| memberships = load_dataset( |
| "parquet", |
| data_files={ |
| "train": ( |
| f"hf://datasets/{repo_id}/memberships/" |
| f"dataset_id={dataset_id}/dedup_bucket={bucket}/*.parquet" |
| ) |
| }, |
| split="train", |
| streaming=True, |
| ) |
| ``` |
|
|
| The same direct form applies to `samples/dedup_bucket=<bucket>/*.parquet` and |
| `assets/dedup_bucket=<bucket>/*.parquet`. |
|
|
| `revision=` is optional for ordinary use because `main` is the current release. |
| For reproducible training, pass the immutable data commit shown below as |
| `revision="4b9c79918adcb426fa7d0b27056fcde9366357af"` to `load_dataset`, or add |
| `@<revision>` to an `hf://` URL. The manifest run ID remains inside |
| `manifest.json` as provenance; it is not part of the Hub path. |
|
|
| The repository-level |
| [V-JEPA-scale pretraining guide](https://github.com/SNU-PI/delta_jepa/blob/main/docs/reference/VJEPA_SCALE_PRETRAINING.md) |
| records the media-materialization boundary, capacity estimates, compute |
| profiles, and launch gates. The guide requires access to the private GitHub |
| repository; this dataset card remains the data-release contract. |
|
|
| ## Exact-dedup boundary |
|
|
| This release removes exact repeated memberships at identical platform, video |
| identity, and millisecond interval keys. It does not merge merely overlapping |
| clips and does not claim perceptual or semantic deduplication. Whole-asset |
| reservation propagation prevents a held-out asset from leaking through another |
| dataset membership. |
|
|
| ## Publication verification |
|
|
| Data commit `4b9c79918adcb426fa7d0b27056fcde9366357af` is the immutable revision for this |
| release. |
| The published tree was checked as 3,293 data objects totaling |
| 41,557,605,070 bytes: 3,292 Parquet shards plus `manifest.json`. Every local |
| object size and SHA-256 matched its remote Hub object. Pinned streaming loads |
| each returned a row from the `samples`, `assets`, and `memberships` |
| configurations; the bare call also resolved to the default `samples` config. |
| The earlier data commit `e3b4f02a422f760995406a0b8e1221e3882ec7d7` is |
| superseded: its `runs/<run_id>` paths remain available in this Hub repository's |
| Git history but no longer resolve on `main`. |
|
|
| ## Media smoke status |
|
|
| One fixed random membership from each included source was probed locally. Six |
| of eleven produced MP4 files that passed `ffprobe` and one-frame CPU decode. |
| Four YouTube-backed rows reached format extraction but failed at the bounded |
| ffmpeg section-request boundary with HTTP 403; the selected EPIC remote seek |
| timed out. This tiny smoke is an integration check, not an estimate of live URL |
| fraction or dataset quality. |
|
|
| ## Planned follow-up |
|
|
| - Extend the pinned streaming-load check from the exercised representative |
| `samples`, `assets`, and `memberships` shards to all 256 sample and asset |
| buckets and every membership partition. |
| - Add DINOv2-L embeddings and a separately versioned perceptual/retrieval dedup |
| layer without rewriting the exact-identity tables. |
| - Define replacement sampling weights only after coverage, duration, role, and |
| availability measurements; do not treat source row counts as mixture weights. |
| - Retry the same failed YouTube smoke IDs with an official yt-dlp EJS runtime |
| and a bounded native-download-then-local-trim fallback. |
| - Add a range-aware EPIC media adapter and repeat the same selected ID. |
| - Run a separately registered, bounded, stratified random-asset reachability |
| measurement for every included source. Preserve the selected asset as the |
| inferential unit, prohibit candidate replacement, and report per-source |
| success fractions with the egress, timestamp, adapter, and uncertainty. |
| - Recover or explicitly retain exclusions for unavailable, gated, or legally |
| withheld sources, including YT-Temporal-1B, LVD-142M, SSv2, Ego4D, |
| Ego-Exo4D, and WebVid. |
| - Decide separately whether source-specific captions and annotations should be |
| published as joinable private tables. They are not required for the current |
| observation-pretraining manifest. |
| - Keep post-training/evaluation manifests separate from this pretraining |
| release; they are intentionally not part of this upload. |
| - Add video-storage or external-stream execution only as a versioned successor |
| after media licensing, availability, codec, and GPU decode policies are |
| fixed. |
|
|
| ## License and access |
|
|
| The repository must remain private while provenance and redistribution terms |
| are audited. Each source retains its own license and access restrictions. A |
| working public URL or community mirror is not, by itself, redistribution |
| permission for metadata or media. |
|
|
