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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Praesent elementum facilisis leo vel fringilla est ullamcorper eget. At imperdiet dui accumsan sit amet nulla facilities morbi tempus.
In the ever-evolving landscape of artificial intelligence (AI) and natural language processing (NLP), the focus on Indic languages, spoken by over a billion people in South Asia, is gaining momentum. Despite their vast user base and cultural significance, Indic languages face numerous challenges, ranging from data scarcity to the lack of sophisticated language tools. In this blog post, we'll delve into Indic Eval, a nimble evaluation suite crafted for appraising Indic LLMs across various tasks. Furthermore, we'll look into a leaderboard equipped with specialized benchmarks to assess and compare the performance of Indic Eval systems. This platform offers a holistic approach to evaluating model efficacy in the Indic language modeling sphere.
In this blog, I am thrilled to share insights into the meticulous approach we undertook to train Amabri Base Cognitive-Lab/Ambari-7B-Instruct-v0.1 and Amabri Instruct Cognitive-Lab/Ambari-7B-Instruct-v0.1. Offering a high-level glimpse into our process, this narrative serves as a precursor to the forthcoming revelation of all technical details— the culmination of extensive testing and evaluation. Stay tuned as we unravel the intricacies that led to the creation of Amabri, an innovative open-source bilingual Kannada-English Large Language Model.
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Praesent elementum facilisis leo vel fringilla est ullamcorper eget. At imperdiet dui accumsan sit amet nulla facilities morbi tempus.
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Praesent elementum facilisis leo vel fringilla est ullamcorper eget. At imperdiet dui accumsan sit amet nulla facilities morbi tempus.
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Praesent elementum facilisis leo vel fringilla est ullamcorper eget. At imperdiet dui accumsan sit amet nulla facilities morbi tempus.
In the ever-evolving landscape of artificial intelligence (AI) and natural language processing (NLP), the focus on Indic languages, spoken by over a billion people in South Asia, is gaining momentum. Despite their vast user base and cultural significance, Indic languages face numerous challenges, ranging from data scarcity to the lack of sophisticated language tools. In this blog post, we'll delve into Indic Eval, a nimble evaluation suite crafted for appraising Indic LLMs across various tasks. Furthermore, we'll look into a leaderboard equipped with specialized benchmarks to assess and compare the performance of Indic Eval systems. This platform offers a holistic approach to evaluating model efficacy in the Indic language modeling sphere.
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