NVIDIA LLM, AI and ML optimized VM


NVIDIA LLM, AI and ML optimized VM


NVIDIA GPU powered Jupyter VM with pre-installed NVIDIA Drivers & Python AI/ML Libraries

Important: For step by step guide on how to setup this vm , please refer to our Getting Started guide

The VM can be provisioned using NVIDIA based GPU instances only. Please select the instance size from the below NVIDIA GPU instance family list or from the Publisher recommendations list available under Plans and Pricing tab of this offer.
  • NCasT4_v3-series
  • NVadsA10 v5-series
  • NVv3-series
  • ND-series
  • NCv3-series

  • Learn more about above GPU instance familiy list from here

    Experience the future of AI/ML development with our NVIDIA GPU-accelerated virtual machine offer.

    Key Features:
    1. CUDA Toolkit from NVIDIA which provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

    2. NVIDIA GPU Acceleration: Unlock unparalleled computing power with our optimized NVIDIA GPU driver setup. Experience lightning-fast performance and accelerated computing for even the most complex AI/ML tasks, enabling you to train & inference LLM models faster and to handle larger datasets with ease.

    3. AI Extensions : Take your AI/ML projects to the next level with Jupyter AI extensions. Seamlessly integrate with over 100 pre-trained models like OpenAI/ChatGPT, GeminiOpenLLM & lot more to unlock new possibilities in LLM & generative AI.

    4. JupyterHub Collaboration: Collaborate effortlessly with colleagues and teammates using JupyterHub's multi-user environment. Share code, data, and insights in real-time, driving innovation and efficiency across your team.

    5. Comprehensive Library Support: Say goodbye to time consuming & tedious library installations - our virtual machine comes pre-configured with all the essential AI/ML libraries you need from TensorFlow to PyTorch and beyond, access the tools you love right out of the box.

    For step by step guide please visit- Getting Started Guide

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