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
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)
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