Building LLMs for languages other than English is in great demand due to the
unavailability and performance of multilingual LLMs, such as understanding the
local context. The problem is critical for low-resource languages due to the
need for instruction sets. In a multilingual country like India, there is a
need for LLMs supporting Indic languages to provide generative AI and LLM-based
technologies and services to its citizens.
This paper presents our approach of i) generating a large Odia instruction
set, including domain knowledge data suitable for LLM fine-tuning, and ii)
building a Llama2-finetuned model tailored for enhanced performance in the Odia
domain. The proposed work will help researchers build an instruction set and
LLM, particularly for Indic languages. We will release the model and
instruction set for the public for research and noncommercial purposes.

本文介绍了我们生成大量 Odia 指令集以及领域知识数据，并构建针对 Odia 领域性能优化的 Llama2 微调模型的方法，这将帮助研究人员构建指令集和 LLM，特别是针对 Indic 语言。我们将为公众提供该模型和指令集，供研究和非商业用途使用。

利用领域知识指令集构建针对奥利亚语的经过 Llama2 微调的 LLM

Building a Llama2-finetuned LLM for Odia Language Utilizing Domain  Knowledge Instruction Set

This paper presents the first publicly available treebank of Odia, a
morphologically rich low resource Indian language. The treebank contains
approx. 1082 tokens (100 sentences) in Odia selected from "Samantar", the
largest available parallel corpora collection for Indic languages. All the
selected sentences are manually annotated following the ``Universal Dependency
(UD)" guidelines. The morphological analysis of the Odia treebank was performed
using machine learning techniques. The Odia annotated treebank will enrich the
Odia language resource and will help in building language technology tools for
cross-lingual learning and typological research. We also build a preliminary
Odia parser using a machine learning approach. The accuracy of the parser is
86.6% Tokenization, 64.1% UPOS, 63.78% XPOS, 42.04% UAS and 21.34% LAS.
Finally, the paper briefly discusses the linguistic analysis of the Odia UD
treebank.

本文提供第一个公开的 Odia 语言树库，并使用机器学习技术对其进行了形态分析。该树库将丰富 Odia 语言资源，有助于建立跨语言学习和分类研究的语言技术工具。本文还构建了一个初步的 Odia 语言分析器，并对 Odia 的 UD 树库进行了简要的语言分析。