Add files using upload-large-folder tool

README.md

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+---
+license: apache-2.0
+task_categories:
+- robotics
+tags:
+- LeRobot
+- language_table
+- openx
+- franka
+configs:
+- config_name: default
+  data_files: data/*.parquet
+---
+Language Table (LeRobot) — Embedding-Only Release
+(DINOv3 + SigLIP2 image features; EmbeddingGemma task-text features)
+
+This repository packages a re-encoded variant of [IPEC-COMMUNITY/viola_lerobot](https://huggingface.co/datasets/IPEC-COMMUNITY/viola_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.
+
+- Robot: Franka
+- Modalities kept: states, actions, timestamps, frame/episode indices, image embeddings, task-text embeddings
+- Removed:
+- observation.images.agentview_rgb
+- observation.images.eye_in_hand_rgb
+- License: apache-2.0 (inherits from source)
+
+----------------------------------------------------------------
+
+Quick Stats
+
+From meta/info.json and meta/task_text_embeddings_info.json:
+
+- Episodes: 135
+- Frames: 68,913
+- Tasks (unique): 3
+- Chunks (original layout): 1 (chunks_size=1000)
+- Shards (this release): 64 Parquet files under data/ (see meta/sharded_index.json)
+- FPS: 20
+- Image embeddings (per frame):
+  - observation.images.agentview_rgb_dinov3 → float32 [1024] (DINOv3 ViT-L/16 CLS)
+  - observation.images.agentview_rgb_siglip2 → float32 [768] (SigLIP2-base)
+  - observation.images.eye_in_hand_rgb_dinov3 → float32 [1024] (DINOv3 ViT-L/16 CLS)
+  - observation.images.eye_in_hand_rgb_siglip2 → float32 [768] (SigLIP2-base)
+- Task-text embeddings (per unique task):
+  - embedding → float32 [768] from google/embeddinggemma-300m
+  - Count: 3 rows (one per task)
+
+Note: This is an embedding-only package. The original pixel arrays listed under “Removed” are dropped.
+
+----------------------------------------------------------------
+
+<details>
+  <summary><b>Contents</b></summary>
+
+<pre>
+. 
+|-- meta/
+|   |-- info.json
+|   |-- sharded_index.json
+|   |-- tasks.jsonl
+|   |-- episodes.jsonl
+|   `-- task_text_embeddings_info.json
+|-- data/
+|   |-- shard-00000-of-000NN.parquet
+|   |-- shard-00001-of-000NN.parquet
+|   |-- ...
+|   `-- task_text_embeddings.parquet
+`-- README.md
+</pre>
+</details>
+
+----------------------------------------------------------------
+
+How This Was Generated (Reproducible Pipeline)
+
+1) Episode → Image Embeddings (drop pixels)
+convert_lerobot_to_embeddings_mono.py (GPU-accelerated preprocessing).
+Adds:
+- observation.images.agentview_rgb_dinov3 (float32[1024])
+- observation.images.agentview_rgb_siglip2 (float32[768])
+- observation.images.eye_in_hand_rgb_dinov3 (float32[1024])
+- observation.images.eye_in_hand_rgb_siglip2 (float32[768])
+Removes:
+- observation.images.agentview_rgb
+- observation.images.eye_in_hand_rgb
+
+2) Task-Text Embeddings (one row per unique task)
+build_task_text_embeddings.py with SentenceTransformer("google/embeddinggemma-300m") → data/task_text_embeddings.parquet + meta/task_text_embeddings_info.json.
+
+3) Data Consolidation (this release)
+All per-episode Parquets were consolidated into N large Parquet shards in one data/ folder.
+- 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.
+- This preserves original addressing while making Hub sync/clone/stream far faster and more reliable.
+
+----------------------------------------------------------------
+
+Metadata (Excerpts)
+
+meta/task_text_embeddings_info.json
+
+~~~json
+{
+  "model": "google/embeddinggemma-300m",
+  "dimension": 768,
+  "normalized": true,
+  "count": 3,
+  "file": "task_text_embeddings.parquet"
+}
+~~~
+
+
+meta/info.json (embedding-only + shards)
+
+~~~json
+{
+  "codebase_version": "v2.1-embeddings-sharded",
+  "robot_type": "franka",
+  "total_episodes": 135,
+  "total_frames": 68913,
+  "total_tasks": 3,
+  "total_videos": 270,
+  "total_chunks": 1,
+  "chunks_size": 1000,
+  "fps": 20,
+  "splits": {
+    "train": "0:135"
+  },
+  "data_path": "data/shard-{shard_id:05d}-of-{num_shards:05d}.parquet",
+  "features": {
+    "observation.state": {
+      "dtype": "float32",
+      "shape": [
+        8
+      ],
+      "names": {
+        "motors": [
+          "motor_0",
+          "motor_1",
+          "motor_2",
+          "motor_3",
+          "motor_4",
+          "motor_5",
+          "motor_6",
+          "motor_7"
+        ]
+      }
+    },
+    "action": {
+      "dtype": "float32",
+      "shape": [
+        7
+      ],
+      "names": {
+        "motors": [
+          "x",
+          "y",
+          "z",
+          "roll",
+          "pitch",
+          "yaw",
+          "gripper"
+        ]
+      }
+    },
+    "timestamp": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "names": null
+    },
+    "frame_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "names": null
+    },
+    "episode_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "names": null
+    },
+    "index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "names": null
+    },
+    "task_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "names": null
+    },
+    "observation.images.agentview_rgb_dinov3": {
+      "dtype": "float32",
+      "shape": [
+        1024
+      ],
+      "names": null
+    },
+    "observation.images.agentview_rgb_siglip2": {
+      "dtype": "float32",
+      "shape": [
+        768
+      ],
+      "names": null
+    },
+    "observation.images.eye_in_hand_rgb_dinov3": {
+      "dtype": "float32",
+      "shape": [
+        1024
+      ],
+      "names": null
+    },
+    "observation.images.eye_in_hand_rgb_siglip2": {
+      "dtype": "float32",
+      "shape": [
+        768
+      ],
+      "names": null
+    }
+  },
+  "video_keys": [
+    "observation.images.agentview_rgb",
+    "observation.images.eye_in_hand_rgb"
+  ],
+  "num_shards": 64,
+  "index_path": "meta/sharded_index.json"
+}
+~~~
+
+----------------------------------------------------------------
+
+Environment & Dependencies
+
+Python ≥ 3.9 • PyTorch ≥ 2.1 • transformers • sentence-transformers • pyarrow • tqdm • decord (and optionally av)
+
+----------------------------------------------------------------
+
+Provenance, License, and Citation
+
+- Source dataset: [IPEC-COMMUNITY/viola_lerobot](https://huggingface.co/datasets/IPEC-COMMUNITY/viola_lerobot)
+- License: apache-2.0 (inherits from the source)
+- Encoders to cite:
+  - facebook/dinov3-vitl16-pretrain-lvd1689m
+  - google/siglip2-base-patch16-384
+  - google/embeddinggemma-300m
+
+----------------------------------------------------------------
+
+Changelog
+
+- 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/task_text_embeddings_info.json

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+{
+  "model": "google/embeddinggemma-300m",
+  "dimension": 768,
+  "normalized": true,
+  "count": 3,
+  "file": "task_text_embeddings.parquet"
+}

meta/tasks.jsonl

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+{"task_index": 0, "task": "pick up the bowl from the lazy Susan and put bowl on the plate"}
+{"task_index": 1, "task": "arrange plate and fork"}
+{"task_index": 2, "task": "make coffee"}