Nemotron-pretraining-Indic-v1

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Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline Hugging Face · 5 hours ago · 50

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October 2026

16 Oct Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline

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Integrated with Open Data Generation Pipeline · 1 source
Derived from Indic continued-pretraining · 1 source
AI4Bharat develops this dataset · 1 source
NVIDIA develops this dataset · 1 source
Nemotron 3.5 Super VL integrated with this dataset · 1 source

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TLDRocket 16 October 2026

AI’s center of gravity this week moved toward something less glamorous than headlines about “smarter” models: scaling the stuff models actually learn from. AI4Bharat and NVIDIA released Nemotron-pretraining-Indic-v1, backed by an open, GPU-accelerated synthetic data generation pipeline for 22 Indian languages. The corpus is massive—about 2.8 trillion tokens—split across 2,601.0 billion native-script tokens and 224.6 billion romanized tokens. The practical pitch is even sharper: builders can reuse not just the data, but the full prompt/quality/repair recipe, then continue-pretraining to push results on Nemotron 3.5 Super VL, with the promise that an Indic continued-pretraining stage helps benchmarks.

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