Airavata: Introducing Hindi Instruction-tuned LLM

Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain, Aswanth Kumar M, Mohammed Safi Ur Rahman Khan +6 more
1/26/2024
cs.CLcs.AI

No official code found. Best implementation: AI4Bharat/IndicInstruct (64 stars, Apache-2.0, last commit 2024-10-26).

Abstract

We announce the initial release of "Airavata," an instruction-tuned LLM for Hindi. Airavata was created by fine-tuning OpenHathi with diverse, instruction-tuning Hindi datasets to make it better suited for assistive tasks. Along with the model, we also share the IndicInstruct dataset, which is a collection of diverse instruction-tuning datasets to enable further research for Indic LLMs. Additionally, we present evaluation benchmarks and a framework for assessing LLM performance across tasks in Hindi. Currently, Airavata supports Hindi, but we plan to expand this to all 22 scheduled Indic languages. You can access all artifacts at https://ai4bharat.github.io/airavata.

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Code Implementations(1)

AI4Bharat/IndicInstructCommunity100%
Apache-2.0

Code repository for "Introducing Airavata: Hindi Instruction-tuned LLM"

6410Shell, PythonJan 22, 20241 years agoApache-2.0
indic-languagesinstruction-tuningmultilingual

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Cite this paper

@article{gala2024airavata,
  title  = {Airavata: Introducing Hindi Instruction-tuned LLM},
  author = {Jay Gala and Thanmay Jayakumar and Jaavid Aktar Husain and Aswanth Kumar M and Mohammed Safi Ur Rahman Khan and Diptesh Kanojia and Ratish Puduppully and Mitesh M. Khapra and Raj Dabre and Rudra Murthy and Anoop Kunchukuttan},
  year   = {2024},
  eprint = {2401.15006},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.15006v2}
}

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