The development of Large Language Models (LLMs) remains heavily skewed towards English and a few other high-resource languages. This linguistic disparity is particularly evident for Bangla - the 5th most spoken language. A few initiatives attempted to create open-source Bangla LLMs with performance still behind high-resource languages and limited reproducibility. To address this gap, we introduce TigerLLM - a family of Bangla LLMs. Our results demonstrate that these models surpass all open-source alternatives and also outperform larger proprietary models like GPT3.5 across standard benchmarks, establishing TigerLLM as the new baseline for future Bangla language modeling.
TigerLLM -- A Family of Bangla Large Language Models
TigerLLM, a family of Bangla Large Language Models, outperforms existing open-source and proprietary models across standard benchmarks.
- Year
- 2025
- Venue
- arXiv 2025
- Authors
- 2
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2503.10995v2ARXIV-DEFAULT
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