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README.md
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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 Challenge](https://
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Download with:
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```
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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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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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{
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