Add dataset card

README.md

@@ -1,29 +1,68 @@
 ---
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
 dataset_info:
   features:
-  - name: text
-    dtype: string
-  - name: id
-    dtype: string
-  - name: url
-    dtype: string
-  - name: language
-    dtype: string
-  - name: language_score
-    dtype: float64
-  - name: fasttext_score
-    dtype: float64
-  - name: dataset
-    dtype: string
+    - name: text
+      dtype: string
+    - name: id
+      dtype: string
+    - name: url
+      dtype: string
+    - name: language
+      dtype: string
+    - name: language_score
+      dtype: float64
+    - name: fasttext_score
+      dtype: float64
+    - name: dataset
+      dtype: string
   splits:
-  - name: train
-    num_bytes: 522435902444
-    num_examples: 89269902
-  download_size: 315974473934
-  dataset_size: 522435902444
+    - name: train
+      num_examples: 89269902
+license: odc-by
+language:
+  - en
+size_categories:
+  - 10M<n<100M
+tags:
+  - pretraining
+  - smol-data
+pretty_name: DCLM 100BT (Shuffled)
 ---
+
+# DCLM 100BT (Shuffled)
+
+A globally shuffled version of [HuggingFaceFW/dclm_100BT](https://huggingface.co/datasets/HuggingFaceFW/dclm_100BT).
+
+Part of the [Smol-Data](https://huggingface.co/collections/HuggingFaceFW/smol-data) collection — tried and tested mixes for strong pretraining.
+
+## Dataset Description
+
+This dataset contains the same ~100B tokens as [dclm_100BT](https://huggingface.co/datasets/HuggingFaceFW/dclm_100BT) but with all documents globally shuffled (seed=42). Use this version when you need randomized document ordering for pretraining.
+
+## How It Was Created
+
+The unshuffled dataset was loaded into memory, shuffled with `dataset.shuffle(seed=42)`, and re-uploaded with 100 shards. See the [smol_data.py](https://github.com/huggingface/datatrove/blob/main/examples/smol_data.py) script for details.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("HuggingFaceFW/dclm_100BT-shuffled", split="train", streaming=True)
+for sample in ds:
+    print(sample["text"][:200])
+    break
+```
+
+## Citation
+
+```bibtex
+@misc{niklaus2025dclm100bt,
+      title={DCLM 100BT},
+      author={Joel Niklaus and Hynek Kydl{\'\i}{\v{c}}ek},
+      year={2026},
+      publisher={Hugging Face},
+      journal={Hugging Face repository},
+      howpublished={\url{https://huggingface.co/datasets/HuggingFaceFW/dclm_100BT-shuffled}}
+}
+```