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  1. README.md +258 -0
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  46. meta/episodes.jsonl +415 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ task_categories:
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+ - robotics
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+ tags:
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+ - LeRobot
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+ - language_table
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+ - openx
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+ - fanuc_mate
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+ configs:
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+ - config_name: default
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+ data_files: data/*.parquet
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+ ---
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+ Language Table (LeRobot) — Embedding-Only Release
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+ (DINOv3 + SigLIP2 image features; EmbeddingGemma task-text features)
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+
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+ This repository packages a re-encoded variant of [IPEC-COMMUNITY/berkeley_fanuc_manipulation_lerobot](https://huggingface.co/datasets/IPEC-COMMUNITY/berkeley_fanuc_manipulation_lerobot) where raw videos are replaced by fixed-length image embeddings, and task strings are augmented with text embeddings. All indices, splits, and semantics remain consistent with the source dataset while storage and I/O are substantially lighter. To make the dataset practical to upload/download and stream from the Hub, we also consolidated tiny per-episode Parquet files into N large Parquet shards under a single data/ folder. The file meta/sharded_index.json preserves a precise mapping from each original episode (referenced by a normalized identifier of the form data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet) to its shard path and row range, so you keep original addressing without paying the small-file tax.
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+
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+ - Robot: fanuc_mate
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+ - Modalities kept: states, actions, timestamps, frame/episode indices, image embeddings, task-text embeddings
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+ - Removed:
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+ - observation.images.image
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+ - observation.images.wrist_image
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+ - License: apache-2.0 (inherits from source)
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+
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+ ----------------------------------------------------------------
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+
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+ Quick Stats
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+
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+ From meta/info.json and meta/task_text_embeddings_info.json:
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+
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+ - Episodes: 415
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+ - Frames: 62,613
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+ - Tasks (unique): 32
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+ - Chunks (original layout): 1 (chunks_size=1000)
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+ - Shards (this release): 64 Parquet files under data/ (see meta/sharded_index.json)
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+ - FPS: 10
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+ - Image embeddings (per frame):
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+ - observation.images.image_dinov3 → float32 [1024] (DINOv3 ViT-L/16 CLS)
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+ - observation.images.image_siglip2 → float32 [768] (SigLIP2-base)
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+ - observation.images.wrist_image_dinov3 → float32 [1024] (DINOv3 ViT-L/16 CLS)
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+ - observation.images.wrist_image_siglip2 → float32 [768] (SigLIP2-base)
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+ - Task-text embeddings (per unique task):
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+ - embedding → float32 [768] from google/embeddinggemma-300m
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+ - Count: 32 rows (one per task)
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+
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+ Note: This is an embedding-only package. The original pixel arrays listed under “Removed” are dropped.
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+
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+ ----------------------------------------------------------------
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+
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+ <details>
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+ <summary><b>Contents</b></summary>
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+
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+ <pre>
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+ .
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+ |-- meta/
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+ | |-- info.json
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+ | |-- sharded_index.json
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+ | |-- tasks.jsonl
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+ | |-- episodes.jsonl
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+ | `-- task_text_embeddings_info.json
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+ |-- data/
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+ | |-- shard-00000-of-000NN.parquet
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+ | |-- shard-00001-of-000NN.parquet
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+ | |-- ...
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+ | `-- task_text_embeddings.parquet
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+ `-- README.md
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+ </pre>
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+ </details>
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+
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+ ----------------------------------------------------------------
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+
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+ How This Was Generated (Reproducible Pipeline)
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+
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+ 1) Episode → Image Embeddings (drop pixels)
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+ convert_lerobot_to_embeddings_mono.py (GPU-accelerated preprocessing).
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+ Adds:
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+ - observation.images.image_dinov3 (float32[1024])
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+ - observation.images.image_siglip2 (float32[768])
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+ - observation.images.wrist_image_dinov3 (float32[1024])
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+ - observation.images.wrist_image_siglip2 (float32[768])
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+ Removes:
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+ - observation.images.image
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+ - observation.images.wrist_image
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+
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+ 2) Task-Text Embeddings (one row per unique task)
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+ build_task_text_embeddings.py with SentenceTransformer("google/embeddinggemma-300m") → data/task_text_embeddings.parquet + meta/task_text_embeddings_info.json.
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+
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+ 3) Data Consolidation (this release)
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+ All per-episode Parquets were consolidated into N large Parquet shards in one data/ folder.
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+ - The index meta/sharded_index.json records, for each episode, its normalized source identifier data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet, the destination shard path, and the (row_offset, num_rows) range inside that shard.
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+ - This preserves original addressing while making Hub sync/clone/stream far faster and more reliable.
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+
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+ ----------------------------------------------------------------
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+
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+ Metadata (Excerpts)
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+
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+ meta/task_text_embeddings_info.json
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+
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+ ~~~json
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+ {
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+ "model": "google/embeddinggemma-300m",
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+ "dimension": 768,
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+ "normalized": true,
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+ "count": 32,
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+ "file": "task_text_embeddings.parquet"
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+ }
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+ ~~~
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+
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+
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+ meta/info.json (embedding-only + shards)
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+
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+ ~~~json
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+ {
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+ "codebase_version": "v2.1-embeddings-sharded",
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+ "robot_type": "fanuc_mate",
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+ "total_episodes": 415,
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+ "total_frames": 62613,
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+ "total_tasks": 32,
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+ "total_videos": 830,
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+ "total_chunks": 1,
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+ "chunks_size": 1000,
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+ "fps": 10,
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+ "splits": {
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+ "train": "0:415"
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+ },
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+ "data_path": "data/shard-{shard_id:05d}-of-{num_shards:05d}.parquet",
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+ "features": {
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+ "observation.state": {
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+ "dtype": "float32",
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+ "shape": [
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+ 8
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+ ],
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+ "names": {
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+ "motors": [
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+ "motor_0",
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+ "motor_1",
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+ "motor_2",
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+ "motor_3",
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+ "motor_4",
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+ "motor_5",
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+ "pad",
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+ "gripper"
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+ ]
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+ }
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+ },
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+ "action": {
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+ "dtype": "float32",
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+ "shape": [
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+ 7
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+ ],
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+ "names": {
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+ "motors": [
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+ "x",
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+ "y",
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+ "z",
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+ "roll",
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+ "pitch",
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+ "yaw",
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+ "gripper"
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+ ]
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+ }
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+ },
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+ "timestamp": {
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+ "dtype": "float32",
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+ "shape": [
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+ 1
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+ ],
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+ "names": null
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+ },
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+ "frame_index": {
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+ "dtype": "int64",
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+ "shape": [
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+ 1
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+ ],
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+ "names": null
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+ },
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+ "episode_index": {
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+ "dtype": "int64",
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+ "shape": [
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+ 1
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+ ],
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+ "names": null
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+ },
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+ "index": {
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+ "dtype": "int64",
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+ "shape": [
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+ 1
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+ ],
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+ "names": null
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+ },
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+ "task_index": {
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+ "dtype": "int64",
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+ "shape": [
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+ 1
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+ ],
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+ "names": null
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+ },
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+ "observation.images.image_dinov3": {
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+ "dtype": "float32",
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+ "shape": [
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+ 1024
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+ ],
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+ "names": null
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+ },
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+ "observation.images.image_siglip2": {
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+ "dtype": "float32",
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+ "shape": [
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+ 768
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+ ],
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+ "names": null
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+ },
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+ "observation.images.wrist_image_dinov3": {
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+ "dtype": "float32",
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+ "shape": [
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+ 1024
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+ ],
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+ "names": null
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+ },
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+ "observation.images.wrist_image_siglip2": {
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+ "dtype": "float32",
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+ "shape": [
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+ 768
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+ ],
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+ "names": null
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+ }
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+ },
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+ "video_keys": [
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+ "observation.images.image",
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+ "observation.images.wrist_image"
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+ ],
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+ "num_shards": 64,
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+ "index_path": "meta/sharded_index.json"
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+ }
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+ ~~~
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+
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+ ----------------------------------------------------------------
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+
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+ Environment & Dependencies
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+
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+ Python ≥ 3.9 • PyTorch ≥ 2.1 • transformers • sentence-transformers • pyarrow • tqdm • decord (and optionally av)
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+
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+ ----------------------------------------------------------------
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+
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+ Provenance, License, and Citation
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+
247
+ - Source dataset: [IPEC-COMMUNITY/berkeley_fanuc_manipulation_lerobot](https://huggingface.co/datasets/IPEC-COMMUNITY/berkeley_fanuc_manipulation_lerobot)
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+ - License: apache-2.0 (inherits from the source)
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+ - Encoders to cite:
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+ - facebook/dinov3-vitl16-pretrain-lvd1689m
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+ - google/siglip2-base-patch16-384
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+ - google/embeddinggemma-300m
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+
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+ ----------------------------------------------------------------
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+
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+ Changelog
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+
258
+ - v2.0-embeddings-sharded — Replaced video tensors with DINOv3 + SigLIP2 features; added EmbeddingGemma task-text embeddings; consolidated per-episode Parquets into N shards with a repo-local index; preserved original indexing/splits via normalized episode identifiers.
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meta/sharded_index.json ADDED
The diff for this file is too large to render. See raw diff
 
meta/task_text_embeddings_info.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
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+ "model": "google/embeddinggemma-300m",
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meta/tasks.jsonl ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {"task_index": 0, "task": "Press the stapler."}
2
+ {"task_index": 1, "task": "Open the drawer."}
3
+ {"task_index": 2, "task": "Pick up the object under the table and put it on top of the table."}
4
+ {"task_index": 3, "task": "Disassemble the object"}
5
+ {"task_index": 4, "task": "Close Water kettle ."}
6
+ {"task_index": 5, "task": "Push the cube to the goal location represented using a cross."}
7
+ {"task_index": 6, "task": "Stack cups together."}
8
+ {"task_index": 7, "task": "Pick up the brush and put it on the table."}
9
+ {"task_index": 8, "task": "Pick up the brush and sweep the table."}
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+ {"task_index": 9, "task": "Close the laptop."}
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+ {"task_index": 10, "task": "Pick up the object and place it in the box."}
12
+ {"task_index": 11, "task": "Separate the stacked cups.."}
13
+ {"task_index": 12, "task": "Pick up the screw driver and place it in the box."}
14
+ {"task_index": 13, "task": "Pick up the object on the table and place it in the cup."}
15
+ {"task_index": 14, "task": "Pick up the banana and place it in the drawer."}
16
+ {"task_index": 15, "task": "Pour the objects in the blue cup to the white cup."}
17
+ {"task_index": 16, "task": "Pick up the level and place it on the cup."}
18
+ {"task_index": 17, "task": "open the box"}
19
+ {"task_index": 18, "task": "Close the drawer."}
20
+ {"task_index": 19, "task": "Handover the object on the table to the human."}
21
+ {"task_index": 20, "task": "Pick up the battery and place it in the open drawer."}
22
+ {"task_index": 21, "task": "Pick up the battery."}
23
+ {"task_index": 22, "task": "Pick up the object on the table then put it down."}
24
+ {"task_index": 23, "task": "Disassemble the object."}
25
+ {"task_index": 24, "task": "Pick up the tape and put it in the box."}
26
+ {"task_index": 25, "task": "Pick up the cup and put it on the table."}
27
+ {"task_index": 26, "task": "Pick up the pen and place it in the cup."}
28
+ {"task_index": 27, "task": "Use the stick to swipe the cup."}
29
+ {"task_index": 28, "task": "Pick up the toy duck and put it on the goal location represented using a cross."}
30
+ {"task_index": 29, "task": "Pick up the two cups together then put them down."}
31
+ {"task_index": 30, "task": "Open the drawer and place the battery in the drawer."}
32
+ {"task_index": 31, "task": "Push the cup the goal location represented using a cross."}