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@@ -5,7 +5,7 @@ size_categories:
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  - 10M<n<100M
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  ---
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- Raw Dataset for the [1X World Model Challenge](https://github.com/1x-technologies/1xgpt).
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  Download with:
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  ```
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  ```
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- Contents of train/val_v2.0:
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-
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  The training dataset is shareded into 100 independent shards. The definitions are as follows:
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  - **video_{shard}.mp4**: Raw video with a resolution of 512x512.
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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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  {
 
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  - 10M<n<100M
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  viewer: false
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  ---
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+ Raw Dataset for the [1X World Model Sammpling Challenge](https://huggingface.co/spaces/1x-technologies/1X_World_Model_Challenge_Sampling).
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  Download with:
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  ```
 
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  ```
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+ ## 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}.mp4**: Raw video with a resolution of 512x512.
 
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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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+ ## Test v2.0
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+
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+ We provide a 250 sample **test_v2.0** dataset for the [World Model Compression Challenge](https://huggingface.co/spaces/1x-technologies/1X_World_Model_Challenge_Sampling) with a similar structure (`video_{shard}.bin`, `states_{shard}.bin`). Use:
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+ - `unpack_data_test.py` to read the test set
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+ - `unpack_data_train_val.py` to read train/val
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+ ---
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  #### Index-to-State Mapping (NEW)
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  ```
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  {