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NE-BERT

NE-BERT is Northeast India's first domain-specific multilingual foundation model. Built on the ModernBERT architecture and trained on 8.3 million sentences, it supports 9 regional languages: Assamese, Khasi, Garo, Manipuri (Meitei), Mizo, Nyishi, Nagamese, Kokborok, and Pnar. It achieves State-of-the-Art performance on regional benchmarks and offers 1.6x faster inference, bridging the digital divide for low-resource languages.

About Model

NE-BERT is a state-of-the-art transformer model designed specifically for the complex, low-resource linguistic landscape of Northeast India. While generic multilingual models (like mBERT or IndicBERT) often underperform on Austroasiatic and Tibeto-Burman languages due to data scarcity, NE-BERT treats these languages as first-class citizens. Supported Languages: The model is trained on a curated corpus of ~8.3 million sentences covering: 1. Assamese [asm] (Indo-Aryan) 2. Manipuri/Meitei [mni] (Tibeto-Burman) 3. Khasi [kha] (Austroasiatic) 4. Mizo [lus] (Tibeto-Burman) 5. Garo [grt] (Tibeto-Burman) 6. Nyishi [njz] (Tibeto-Burman) 7. Nagamese Creole [nag] (Indo-Aryan) 8. Kokborok [trp] (Tibeto-Burman) 9. Pnar [pbv] (Austroasiatic) Technical Key Features: * Architecture: ModernBERT-Base (Pre-Norm, Rotary Embeddings, Flash Attention 2) * Context Window: Supports up to 8,192 tokens * Efficiency: 1.6x more efficient tokenization than mBERT * Performance: Low perplexity on Austroasiatic and Tibeto-Burman languages

NE-BERT

Metadata Metadata

Attribution 4.0 International (CC BY- 4.0)

MWirelabs

Transformers

PyTorch

Open

MWire Labs

Arts, Culture and Tourism

22/11/25 13:08:10

Badal Nyalang

0

Activity Overview Activity Overview

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  • Redirect 18
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Tags Tags

  • modernbert
  • Masked Language Modeling
  • northeast-india
  • low-resource-NLP
  • northeast bert
  • mwirelabs
  • token-efficiency
  • Assamese
  • Garo
  • Nyishi
  • Meitei
  • Nagamese
  • khasi
  • A'chik
  • Mizo
  • kokborok
  • Pnar

License Control License Control

Attribution 4.0 International (CC BY- 4.0)

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