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SOFTWARE
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Software optimization and co-design for H100 GPU maximum potential
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yea, I expect a healthy amount of software work and co-design to use the H100 to its maximum potential!
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Deploy LLM Applications as Extensions in Google Sheets
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LLM applications can also be deployed as extensions to existing applications. You'll learn about two such extensions, the first one being Google Apps Script for Google Sheets. You'll learn how to build a text classifier and summarizer right inside Google Sheets.
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Build AI-Powered Chrome Extension for Web Page Summarization
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Next, you'll learn how to create a Google Chrome extension that summarizes the text content of a web page. With this extension, for every web page that a user visits, a summary of the page’s content will be displayed at the top.
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Deploy Cohere Models on AWS SageMaker Studio Securely
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Cohere’s models are also available via Amazon SageMaker. This provides a solution for deploying use cases in a private and secure environment. In this module, you’ll learn how to create a product description generator endpoint on SageMaker via Amazon SageMaker Studio.
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Deploying Topic Modeling Applications with Databutton
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Next, you'll learn how to deploy a topic modeling application with Databutton. Databutton supports Streamlit, but also has additional features to make deploying applications simple, such as Libraries for storing reusable code and Data Storage for a simple put/get data store.
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Building LLM-Powered APIs with FastAPI for Sentiment Analysis
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For building more serious applications, you’ll want to set up an LLM-powered back-end as endpoints. FastAPI lets you do that. It is a web framework for building APIs with Python. In this next module, you'll learn how to create a sentiment analysis classifier API with FastAPI.
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Building AI User Interfaces with Streamlit and Cohere
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Looking to build user interfaces that users can interact with? You'll begin with one of the fastest and simplest options to get started: Streamlit. You’ll learn how to build a startup idea generator with a Cohereand Streamlit and then deploy it on Streamlit Cloud.
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Deploying LLM-Powered Applications: Platform Options Guide
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Are you wondering what options are available out there for deploying LLM-powered applications? In http://
llm.university’s latest module, Deployment, you’ll learn how to deploy applications on several platforms and frameworks. Let’s take a look at what you’ll learn.