NAME0x0/hagi-fineweb-edu-smollm2

HAGI - Tokenized HuggingFaceFW/fineweb-edu (SmolLM2-135M tokenizer)

Pre-tokenized token-id shards used to train the HAGI Stage 0 baseline and the Grade-Decomposed Recurrence ablation (models A/B/C/D). A tokenized derivative of HuggingFaceFW/fineweb-edu subset sample-10BT, published so the exact training corpus loads identically in any environment (Colab, Kaggle, local) with no re-tokenization and no Google Drive access.

Format - read before using

• Files: shard_NNNNN.bin - a flat little-endian uint16 stream of token ids, no header, documents separated by the tokenizer's EOS id. Read via numpy.memmap.
• Tokenizer: HuggingFaceTB/SmolLM2-135M - vocab 49,152 (fits uint16). Shards tokenized with any other tokenizer are incompatible: the ids would index the wrong embeddings (silent garbage), so do not mix sources.
• Token count of a shard: filesize / 2.
• Held-out convention: the last shard (shard_00006.bin) is reserved as validation; train on the rest.

Contents

• Shards: 7
• Total tokens: ~630,891,027

Shard	Tokens
shard_00000.bin	100,694,996
shard_00001.bin	100,686,108
shard_00002.bin	100,677,968
shard_00003.bin	100,324,700
shard_00004.bin	100,641,381
shard_00005.bin	100,534,502
shard_00006.bin	27,331,372

Load

from huggingface_hub import snapshot_download
path = snapshot_download(repo_id="NAME0x0/hagi-fineweb-edu-smollm2", repo_type="dataset", allow_patterns="*.bin")
# point training at the returned directory:
#   python -m prototype.training.train --config configs/ablation_b.yaml --data <path> ...

MemmapTokenDataset (prototype/data/dataset.py) consumes this directory directly.

Models trained on this data

• Stage 0 baseline: https://huggingface.co/NAME0x0/hagi-stage0
• Ablation: -a / -b / -c / -d

License & attribution

Derivative of HuggingFaceFW/fineweb-edu (sample-10BT), released under ODC-By 1.0 - the upstream license. Attribute FineWeb-Edu (HuggingFaceFW) on use. Tokenization adds no new content; it only maps text to HuggingFaceTB/SmolLM2-135M ids.