Embark on a wild race with Gemma as we explore the exciting (and sometimes slow) world of running Google's open-source large language model! We'll test drive different methods, from the leisurely pace of Ollama on a local machine to the speedier Groq platform. Join us as we compare these approaches, analyzing performance, costs, and ease of use for developers working with LLMs. Will the tortoise or the hare win this race?

Learn more:

* Model card: https://console.cloud.google.com/vertex-ai/publishers/google/model-garden/335

* Ollama: https://ollama.com/

* LangChain.js with Ollama: https://js.langchain.com/docs/integrations/llms/ollama

* Groq: https://groq.com/

Timestamps:

0:00:00 - Introduction

0:03:05 - Getting to Know Gemma: Exploring the Model Card

0:05:30 - Vertex AI Endpoint: Fast Deployment, But at What Cost?

0:13:40 - Ollama: The Tortoise of Local LLM Hosting

0:17:40 - LangChain Integration: Adding Functionality to Ollama

0:21:44 - Groq: The Hare of LLM Hardware

0:26:06 - Comparing Approaches: Speed vs. Cost vs. Control

0:27:35 - Future of Open LLMs and Google Cloud Next

#GemmaSprint

This project was supported, in part, by Cloud Credits from Google