Deploy Llama 3 with Vertex AI Model Garden โ€” WalkSelf
โฑ 2 oras 30 min ๐Ÿ“š 25 aralin ๐ŸŽง Audio version

Deploy Llama 3 with Vertex AI Model Garden

Learn to configure, deploy, and query open foundation models on Vertex AI dedicated inference endpoints.

  • ๐Ÿ’ฌ AI instructor
    Magtanong tungkol sa anumang aralin at makakuha ng malinaw na sagot agad, anumang oras.
  • ๐Ÿ• Magsimula anumang oras
    Walang iskedyul o deadline โ€” mag-aral sa sarili mong bilis, kahit kailan.
  • ๐ŸŒ Sa Filipino
    Mga aralin, gawain at sertipiko โ€” lahat ay ganap na nasa wika mo.

Tungkol sa kursong ito

Deploying modern large language models requires a practical understanding of managed cloud infrastructure, model registries, and endpoint configuration. This text-based course guides you through the process of launching Llama 3 on Vertex AI Model Garden for reliable, real-time inference. What you'll learn: - Understand foundational terminology and concepts behind cloud-hosted language models - Navigate Model Garden to locate and configure open foundation models - Select appropriate compute hardware, machine types, and accelerators for model serving - Deploy Llama 3 to dedicated online prediction endpoints - Query your live endpoint using REST APIs and Python client code - Apply basic monitoring, cost optimization, and endpoint management techniques The reading begins with core architectural concepts before moving into step-by-step endpoint deployment, request formatting, and practical integration examples. Designed for developers, data practitioners, and cloud beginners, no prior machine learning operations experience is required. Start reading to master open-source model deployment on Vertex AI.

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    Idagdag sa LinkedIn profile mo
  • ๐Ÿ’ฌ Personal na AI tutor
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  • ๐ŸŽง Kasama ang audio version
    Mag-aral kahit saan โ€” hindi kailangan ng screen
  • โ™พ๏ธ Lifetime access
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  • ๐Ÿ“ฑ Telepono o computer
    Gumagana saanman, kahit anong device
  • ๐Ÿ’ธ 14-day refund
    Walang tanong
  • โšก Maikli at focused
    2 oras 30 min ng practical content

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