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README.md
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huggingface-cli download 1x-technologies/worldmodel --repo-type dataset --local-dir data
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```
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**Current version: v2.0**
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Changes from v1.1:
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- New train and val dataset of 100 hours, replacing the v1.1 datasets
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- Blur applied to faces
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Contents of train/val_v2.0:
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The training dataset is shareded into 100 independent shards. The
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- **metadata** - The `metadata.json` file provides high-level information about the entire dataset, while `metadata_
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#### Index-to-State Mapping (NEW)
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```
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huggingface-cli download 1x-technologies/worldmodel --repo-type dataset --local-dir data
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```
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Changes from v1.1:
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- New train and val dataset of 100 hours, replacing the v1.1 datasets
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- Blur applied to faces
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Contents of train/val_v2.0:
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The training dataset is shareded into 100 independent shards. The definitions are as follows:
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- **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".
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- **segment_idx_{shard}.bin** - Maps each frame `i` to its corresponding segment index. You may want to use this to separate non-contiguous frames from different videos (transitions).
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- **states_{shard}.bin** - States arrays (defined below in `Index-to-State Mapping`) stored in `np.float32` format. For frame `i`, the corresponding state is represented by `states_{shard}[i]`.
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- **metadata** - The `metadata.json` file provides high-level information about the entire dataset, while `metadata_{shard}.json` files contain specific details for each shard.
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#### Index-to-State Mapping (NEW)
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```
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