Datasets:

Fredtt3
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LLaDA-Sample-10BT

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Dataset: LLaDA-Sample-10BT
Base: HuggingFaceFW/fineweb (subset sample-10BT)
Purpose: Training LLaDA (Large Language Diffusion Models)

Preprocessing

Tokenizer: GSAI-ML/LLaDA-8B-Instruct
Chunking: Up to 4,096 tokens per chunk (1% of chunks randomly sized between 1–4,096 tokens)
Noisy masking: Applied with noise factor ε = 1×10⁻³
Fields per chunk (PyTorch tensors):
- input_ids
- noisy_input_ids
- mask
- t (time scalar)

Statistics

Total chunks: ~2,520,000
Shards: 252 .pt files
Chunks per file: 10,000
Average file size: ~702–708 MB
Total size: ~166 GB

Usage

This dataset is used for training in the LLaDA-from-scratch GitHub repository, where you’ll find the full data pipeline and training scripts.