FredyRivera-dev/LLaDA-Sample-10BT

Dataset: LLaDA-Sample-10BTBase: 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… See the full description on the dataset page: https://huggingface.co/datasets/FredyRivera-dev/LLaDA-Sample-10BT.

<iframe src="https://silytics.si/embed/item/dbd3cce1-48c3-4717-ba06-f781536540e6" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.