Update README.md

README.md

@@ -1,66 +1,72 @@
----
-license: odc-by
-task_categories:
-- text-generation
-language:
-- en
-tags:
-- redpajama
-- v2
-- 1B
-- parquet
-size_categories:
-- 1B<n<10B
----
-
-# RedPajama-Data-V2 1B
-
-## Dataset Description
-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.
-
-## Motivation
-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.
-
-## Dataset Details
-- **Total Tokens:** 1,005,000,066 (~1.01B)
-- **Source:** [togethercomputer/RedPajama-Data-V2](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2) (config: `sample-10B`)
-- **Structure:** Randomized slice of the source dataset.
-- **Format:** Parquet (Snappy compression)
-- **Producer:** Kris Bailey (kris@krisbailey.com)
-
-## Usage
-
-```python
-from datasets import load_dataset
-
-ds = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train")
-print(ds[0])
-```
-
-## Subsets & Slicing
-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.
-
-```python
-# 100M Token Subset (approx 10%)
-ds_100m = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train[:10%]")
-
-# 500M Token Subset (approx 50%)
-ds_500m = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train[:50%]")
-```
-
-## Citation
-```bibtex
-@article{together2023redpajama,
-  title={RedPajama: An Open Source Recipe to Reproduce LLaMA training dataset},
-  author={Together Computer},
-  journal={https://github.com/togethercomputer/RedPajama-Data},
-  year={2023}
-}
-```
-
-## Data Mixture
-
-| Subset | Tokens | % of Total |
-| :--- | :--- | :--- |
-| `redpajama-v2-sample` | 1,005,000,066 | 100.00% |
-| **Total** | **1,005,000,066** | **100.00%** |
+---
+license: odc-by
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- redpajama
+- v2
+- 1B
+- parquet
+- redpajama
+- reference-reproduction
+- benchmark-subset
+- open-pretraining-data
+- reproducible-dataset
+- data-slicing
+size_categories:
+- 1B<n<10B
+---
+
+# RedPajama-Data-V2 1B
+
+## Dataset Description
+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.
+
+## Motivation
+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.
+
+## Dataset Details
+- **Total Tokens:** 1,005,000,066 (~1.01B)
+- **Source:** [togethercomputer/RedPajama-Data-V2](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-V2) (config: `sample-10B`)
+- **Structure:** Randomized slice of the source dataset.
+- **Format:** Parquet (Snappy compression)
+- **Producer:** Kris Bailey (kris@krisbailey.com)
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train")
+print(ds[0])
+```
+
+## Subsets & Slicing
+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.
+
+```python
+# 100M Token Subset (approx 10%)
+ds_100m = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train[:10%]")
+
+# 500M Token Subset (approx 50%)
+ds_500m = load_dataset("krisbailey/RedPajama-Data-V2-1B", split="train[:50%]")
+```
+
+## Citation
+```bibtex
+@article{together2023redpajama,
+  title={RedPajama: An Open Source Recipe to Reproduce LLaMA training dataset},
+  author={Together Computer},
+  journal={https://github.com/togethercomputer/RedPajama-Data},
+  year={2023}
+}
+```
+
+## Data Mixture
+
+| Subset | Tokens | % of Total |
+| :--- | :--- | :--- |
+| `redpajama-v2-sample` | 1,005,000,066 | 100.00% |
+| **Total** | **1,005,000,066** | **100.00%** |