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tokenizer
string
vocab_size
int64
num_tokens
int64
source
string
dtype
string
rustbpe
65,536
20,000,000,000
fineweb
uint16

fineweb-nanochatbpe-20B

FineWeb-Edu (from karpathy/fineweb-edu-100b-shuffle), 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 20,000,000,000
val.bin val 52,336,096

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:

from huggingface_hub import hf_hub_download
import numpy as np

path = hf_hub_download(repo_id="stanpony/fineweb-nanochatbpe-20B", filename="train.bin", repo_type="dataset")
tokens = np.memmap(path, dtype="uint16", mode="r")
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