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FORGE-3B Pretraining Data

Tokenized and packed pretraining data for the FORGE-3B language model.

Stats

  • Total tokens: 51.4070B
  • Domains: 10/10
  • Sequence length: 2048 tokens
  • Format: .npy shards of shape (N, 2048) with dtype uint32
  • Tokenizer: CRAYON (xerv-crayon, standard profile)

Domain Breakdown

Domain Weight Tokens (B) Status
fineweb_edu 30% 15.0008
thestack 16% 8.0011
wikipedia 8% 4.2791
openwebmath 8% 3.9654
books 7% 2.8713
arxiv 6% 6.6620
dolma 10% 5.0003
stackexchange 5% 2.5002
redpajama_cc 6% 1.1264
multilingual 4% 2.0002

Usage

import numpy as np
from huggingface_hub import hf_hub_download

# Download a shard
path = hf_hub_download(
    repo_id="Phase-Technologies/forge-3b-pretrain-data",
    filename="fineweb_edu/train_shard_0000.npy",
    repo_type="dataset",
)
data = np.load(path)  # shape: (50000, 2048), dtype: uint32

Structure

Phase-Technologies/forge-3b-pretrain-data/
├── fineweb_edu/     (30%, 15B tokens)
├── thestack/        (16%, 8B tokens)
├── wikipedia/       (8%, 4B tokens)
├── openwebmath/     (8%, 4B tokens)
├── books/           (7%, 3.5B tokens)
├── arxiv/           (6%, 3B tokens)
├── dolma/           (10%, 5B tokens)
├── stackexchange/   (5%, 2.5B tokens)
├── redpajama_cc/    (6%, 3B tokens)
├── multilingual/    (4%, 2B tokens)
└── preprocessing_manifest.json
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