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Key terms

H2O LLM DataStudio uses several key terms across its documentation, and each, in turn, is explained in the sections below.

LLM (Large Language Model)​

A LLM refers to advanced AI models excelling in natural language understanding and generation, utilizing vast neural networks and extensive training data.

Tokenization​

A process that breaks down text into smaller units, called tokens, to facilitate natural language processing tasks. Each token can be a word, subword, or character, allowing language models to analyze and understand text more effectively.

Truncation​

The process of shortening text by removing characters from the beginning or end of a sequence, commonly used to fit text within specified length constraints or to prepare input data for language models with fixed input size.

RLHF (Reinforcement Learning with Human Feedback)​

A training technique for Large Language Models (LLMs) that combines pre-training on a large corpus with fine-tuning on task-specific datasets, enhancing model performance for various tasks.

Augmentation​

Augmentation allows you to blend your datasets with other publicly available datasets for the purpose of obtaining variety. In some cases, you can integrate your datasets with RLHF related datasets, to add more domain aspects. The Augment tab shows a catalog of rich datasets which can be used immediately in the Prepare pipeline. You can also bring your own datasets for the augmentation process. For more information, see Augment.

HAMC​

H2O AI Managed cloud is the main platform for users whereas H2O Admin Center is connected with the application that customers can use to configure their dedicated cloud deployment based on business use cases. H2O Admin Center supports firewall management and user management.

The fully managed solution of the H2O AI Cloud has all the same features to make, operate, and innovate with your own AI. The infrastructure and software management of the application are completely handled by H2O.ai allowing the customer to focus on solving their business problems with AI.

These new features include:

  • A completely dedicated cloud environment for each customer.
  • All operation activities (installation, upgrades, day-to-day operations) are handled by H2O.ai.
  • Monitoring and automatic alerts of resource consumption.
  • Quick onboarding process.
  • Protection of public resources with several layers of security including DDoS protection, web application firewall, and firewalls.
  • Optional security control of who can access resources by include-listing specific IP addresses.

Most users prefer controlling the application in a self-service manner so users get access to their account as well as inbound/outbound rules for moving data in/out of the platform.

H2O Managed Cloud is designed for high availability and dependability, providing tools to:

  • Develop AI based applications
  • Deploy AI based applications
  • Manage AI based applications
  • Maintain AI based applications

Which helps protect the confidentiality, integrity, and availability of your systems and data is our top priority.

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