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Added New Clouder Ai Tutorials. #14
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@@ -4,7 +4,8 @@ In this lab, we will go through LLM Chatbot AMP using Cloudera Machine Learning | |
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1. On login, you will be taken to Trials Home Page | ||
2. Click, **Start Trial** go to your Machine Learning Workspace | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This is actually true. For CAII you need to click on the 9dot menu on the topleft corner. Can we make a note about that? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Machine Learning Workspace -> |
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3. [Here](https://app.getreprise.com/launch/MXxjDe6/) is the Reprise demo with step by step tutorial for the LLM Chatbot | ||
3. [Here](https://app.getreprise.com/launch/MXxjDe6/) is the Reprise demo with step by step tutorial for the LLM Chatbot | ||
4. [Here](https://app.getreprise.com/launch/dyR7W26/) is the Reprise demo showcasing Cloudera AI Inference capabilities. | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Why are we adding this here? This page talks about the first reprise. What's the flow users go through? |
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[Here](https://github.com/cloudera/CML_AMP_LLM_Chatbot_Augmented_with_Enterprise_Data) is more detailed information of the LLM Chatbot | ||
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# Cloudera AI Inference service | ||
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[Here](https://app.getreprise.com/launch/dyR7W26/) is an interactive Reprise demo showcasing Cloudera AI Inference capabilities. | ||
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In this lab, you'll explore how to leverage Cloudera's AI Inference service for enterprise-grade LLM deployment. The demo walks you through: | ||
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1. Navigating the Model Hub to discover and select pre-optimized LLMs | ||
2. Deploying a selected model in a secure, private environment using the AI Inference service | ||
3. Configuring deployment settings for optimal performance and resource utilization | ||
4. Connecting the deployed model to your AI Applications through standard APIs | ||
5. Testing the model with sample queries to demonstrate performance and accuracy | ||
6. Monitoring inference metrics and scaling resources as needed | ||
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This demo highlights how Cloudera AI simplifies the process of bringing powerful LLMs into your production environment with enterprise-grade security, governance, and performance. |
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Line 3 ->
Cloudera Machine Learning (CML) ->
Cloudera AI Workbench