Update README.md

README.md

@@ -12,6 +12,8 @@ Download with:
 huggingface-cli download 1x-technologies/worldmodel --repo-type dataset --local-dir data
 ```
 
+**Current version: v2.0**
+
 Changes from v1.1:
 - New train and val dataset of 100 hours, replacing the v1.1 datasets
 - Blur applied to faces
@@ -20,7 +22,7 @@ Contents of train/val_v2.0:
 
 The training dataset is shareded into 100 independent shards. The shapes and definitions of the arrays are as follows (N is the number of frames).
 
-- **video_{shard}.bin**: 8x8x8 image patches at 30hz, with 17 frame temporal window, encoded using [NVIDIA Cosmos Tokenizer](https://github.com/NVIDIA/Cosmos-Tokenizer) "Cosmos-Tokenizer-DV8x8x8".
+- **videos**: 8x8x8 image patches at 30hz, with 17 frame temporal window, encoded using [NVIDIA Cosmos Tokenizer](https://github.com/NVIDIA/Cosmos-Tokenizer) "Cosmos-Tokenizer-DV8x8x8".
 - **segment_indicies** - For video `n` and frame `i`, `segment_idx_n[i]` uniquely points to the segment index that frame `i` came from. You may want to use this to separate non-contiguous frames from different videos (transitions).
 - **robot_states** - States arrays defined in `Index-to-State Mapping` stored in `np.float32` format. For video `n` and frame `i`, the corresponding state is given by `states_n[i]`.
 - **metadata** - The `metadata.json` file provides high-level information about the entire dataset, while `metadata_[n].json` files contain specific details for each individual video `n`.