h2oGPTe Starter Track: Final Recap
- Generative AI
- Enterprise h2oGPTe
This lesson recaps the H2O Generative AI Starter Track by walking back through its core skills in Enterprise h2oGPTe. It covers prompting with reusable prompt templates, ingesting documents, audio, images, and websites into collections across more than 65 supported file types, and using retrieval augmented generation to ground answers in that uploaded data. It revisits the Configuration tab for selecting a language model and tuning parameters, and the API for building custom applications on top of h2oGPTe. It closes by pointing learners to h2o.ai/university for further courses on the platform.
Key takeaways
- How prompt templates act as reusable blueprints for getting consistent responses from h2oGPTe
- What Collections support, ingesting over 65 file types including documents, audio, images, and websites
- Why RAG matters for grounding responses in your own uploaded data rather than general knowledge
- How the Configuration tab lets you select a language model and tune generation parameters
- The API lets developers build custom applications directly on top of h2oGPTe
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