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README.md

@@ -0,0 +1,31 @@
+---
+pretty_name: github-code-nanochatbpe-1B
+language:
+- en
+tags:
+- pretokenized
+- language-modeling
+size_categories:
+- 1B<n<10B
+---
+
+# github-code-nanochatbpe-1B
+
+**GitHub Code (all-all)** (from [`codeparrot/github-code`](https://huggingface.co/datasets/codeparrot/github-code)), pre-tokenized with the `nanochatbpe` tokenizer (vocab 65,536) and packaged as flat `uint16` token-id `.bin` files for fast memmap training.
+
+| file | split | tokens |
+| --- | --- | --- |
+| `train.bin` | train | 1,000,000,000 |
+| `val.bin` | val | 10,000,000 |
+
+`train` and `val` are disjoint held-out partitions. Each `.bin` is a raw little-endian `uint16` stream (no header); token count = `filesize / 2`, and `train.meta.json` / `val.meta.json` carry the full metadata. The `tokenizer/` files (when present) are the exact tokenizer used to produce these ids.
+
+**Load a bin** with the standard Hugging Face downloader:
+
+```python
+from huggingface_hub import hf_hub_download
+import numpy as np
+
+path = hf_hub_download(repo_id="alexkstern/github-code-nanochatbpe-1B", filename="train.bin", repo_type="dataset")
+tokens = np.memmap(path, dtype="uint16", mode="r")
+```