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Fine Tuning The H2O Danube2 LLM for The Singlish Language
by Dipam Chakraborty, Kavindu Warnakulasuriya, Jordan Seow | June 03, 2024 H2O Danube, Large Language Models

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Boosting LLMs to New Heights with Retrieval Augmented Generation

Businesses today can make leaps and bounds to revolutionize the way things are done with the use of Large Language Models (LLMs). LLMs are widely used by businesses today to automate certain tasks and create internal or customer-facing chatbots that boost efficiency. Challenges with dynamic adaption of LLMs As with any new hyped-up thing that […]

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Testing Large Language Model (LLM) Vulnerabilities Using Adversarial Attacks
by Kim Montgomery, Pramit Choudhary, Michal Malohlava | July 19, 2023 Generative AI, H2O LLM Studio, LLM Limitations, LLM Robustness, LLM Safety, Large Language Models, Responsible AI

Adversarial analysis seeks to explain a machine learning model by understanding locally what changes need to be made to the input to change a model’s outcome. Depending on the context, adversarial results could be used as attacks, in which a change is made to trick a model into reaching a different outcome. Or they could be used as an exp...

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H2O LLM EvalGPT: A Comprehensive Tool for Evaluating Large Language Models
by Srinivas Neppalli, Abhay Singhal, Michal Malohlava | July 19, 2023 Generative AI, Large Language Models, h2oGPT

In an era where Large Language Models (LLMs) are rapidly gaining traction for diverse applications, the need for comprehensive evaluation and comparison of these models has never been more critical. At H2O.ai, our commitment to democratizing AI is deeply ingrained in our ethos, and in this spirit, we are thrilled to introduce our innovati...

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H2O LLM DataStudio: Streamlining Data Curation and Data Preparation for LLMs related tasks
by Shivam Bansal, Sanjeepan Sivapiran, Nishaanthini Gnanavel | June 14, 2023 Data, Data Preparation, H2O LLM Studio, Large Language Models, NLP, h2oGPT

A no-code application and toolkit to streamline data preparation tasks related to Large Language Models (LLMs) H2O LLM DataStudio is a no-code application designed to streamline data preparation tasks specifically for Large Language Models (LLMs). It offers a comprehensive range of preprocessing and preparation functions such as text cl...

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Democratization of LLMs
by Sri Ambati | May 08, 2023 H2O LLM Studio, Large Language Models, h2oGPT

Every organization needs to own its GPT as simply as we need to own our data, algorithms and models. H2O LLM Studio democratizes LLMs for everyone allowing customers, communities and individuals to fine-tune large open source LLMs like h2oGPT and others on their own private data and on their servers. Every nation, state and city needs it...

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Building the World's Best Open-Source Large Language Model: H2O.ai's Journey
by Arno Candel | May 03, 2023 Large Language Models, h2oGPT

At H2O.ai, we pride ourselves on developing world-class Machine Learning, Deep Learning, and AI platforms. We released H2O, the most widely used open-source distributed and scalable machine learning platform, before XGBoost, TensorFlow and PyTorch existed. H2O.ai is home to over 25 Kaggle grandmasters, including the current #1. In 2017, w...

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Effortless Fine-Tuning of Large Language Models with Open-Source H2O LLM Studio
by Parul Pandey | May 01, 2023 H2O LLM Studio, Large Language Models

While the pace at which Large Language Models (LLMs) have been driving breakthroughs is remarkable, these pre-trained models may not always be tailored to specific domains. Fine-tuning — the process of adapting a pre-trained language model to a specific task or domain—plays a critical role in NLP applications. However, fine-tuning can be ...

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