Expose compact manifest indexes as dataset configs

README.md

@@ -23,6 +23,18 @@ configs:
     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
@@ -82,13 +94,13 @@ 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 three named
+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"` or
-`"memberships"` for the other schemas.
+`"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.
 
-Assign the 256 hash buckets across workers so each worker opens only its own
-shards:
+The simplest streaming load is:
 
 ```python
 from datasets import load_dataset
@@ -105,18 +117,19 @@ web_train = samples.filter(
 )
 ```
 
-For source lineage, load the memberships configuration and filter by
-`dataset_id`, or address a source partition directly when minimizing shard
-discovery matters:
+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}/**/*.parquet"
+            f"dataset_id={dataset_id}/dedup_bucket={bucket}/*.parquet"
         )
     },
     split="train",
@@ -124,9 +137,12 @@ memberships = load_dataset(
 )
 ```
 
+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="5f0920c3f4edbe7b33e774cb9af445aa4a5b10a0"` to `load_dataset`, or add
+`revision="CONFIG_COMMIT_PENDING"` 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.
 
@@ -140,13 +156,15 @@ dataset membership.
 
 ## Publication verification
 
-Data commit `5f0920c3f4edbe7b33e774cb9af445aa4a5b10a0` is the immutable revision for this
-release. The upload was checked as 3,293 data objects totaling
+Data commit `CONFIG_COMMIT_PENDING` 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 one
-representative `samples` shard, one `assets` shard, and one `memberships`
-partition.
+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