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--- |
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license: odc-by |
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task_categories: |
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- text-generation |
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language: |
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- en |
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tags: |
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- redpajama |
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- v2 |
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- 1B |
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- parquet |
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- redpajama |
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- reference-reproduction |
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- benchmark-subset |
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- open-pretraining-data |
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- reproducible-dataset |
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- data-slicing |
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size_categories: |
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- 1B<n<10B |
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--- |
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# RedPajama-Data-V2 1B |
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## Dataset Description |
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This is a **1.01 Billion token** subset of the [togethercomputer/RedPajama-Data-V2](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2) dataset (specifically derived from the `sample-10B` config). It was created by randomly sampling the source data. |
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## Motivation |
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RedPajama V2 is a state-of-the-art web dataset with rich quality signals. This 1B token subset allows for rapid testing of these quality signals or other filtering experiments without needing to process the full multi-trillion token dataset. |
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## Dataset Details |
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- **Total Tokens:** 1,005,000,066 (~1.01B) |
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- **Source:** [togethercomputer/RedPajama-Data-V2](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2) (config: `sample-10B`) |
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- **Structure:** Randomized slice of the source dataset. |
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- **Format:** Parquet (Snappy compression) |
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- **Producer:** Kris Bailey (kris@krisbailey.com) |
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## Usage |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train") |
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print(ds[0]) |
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``` |
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## Subsets & Slicing |
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Since this dataset was randomly shuffled during creation, you can safely slice it to get smaller, representative datasets (e.g., for scaling laws experiments) without needing to download the full dataset. |
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```python |
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# 100M Token Subset (approx 10%) |
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ds_100m = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train[:10%]") |
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# 500M Token Subset (approx 50%) |
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ds_500m = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train[:50%]") |
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``` |
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## Citation |
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```bibtex |
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@article{together2023redpajama, |
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title={RedPajama: An Open Source Recipe to Reproduce LLaMA training dataset}, |
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author={Together Computer}, |
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journal={https://github.com/togethercomputer/RedPajama-Data}, |
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year={2023} |
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} |
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``` |
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## Data Mixture |
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| Subset | Tokens | % of Total | |
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| :--- | :--- | :--- | |
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| `redpajama-v2-sample` | 1,005,000,066 | 100.00% | |
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| **Total** | **1,005,000,066** | **100.00%** | |
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