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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:
.npyshards of shape(N, 2048)with dtypeuint32 - 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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