README.md

metadata

license: apache-2.0
task_categories:
  - text-generation
language:
  - en
  - de
  - fr
  - es
  - zh
  - ja
  - ru
  - pt
  - it
  - nl
  - ar
tags:
  - forge-3b
  - pretraining
  - tokenized
  - packed
size_categories:
  - 10B<n<100B

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