Q Blocks Documentation
  • 👋Welcome to Q Blocks
  • 🌐GPU Computing at Scale
  • 💻Launch a Q Blocks GPU instance
    • Using Dashboard UI
    • Using Rest APIs
  • 💰GPU Instance Pricing
  • 🤖Fine-tuning Falcon 7B/40B LLM
  • 🔑IAM: Share access with team
  • 🤔Q Blocks How To Guide
    • Create a new user
    • Upload data using SCP command
    • Use Visual Studio Code with Q Blocks instances
    • Port forwarding to run web services
    • Launch Jupyter Hub in Q Blocks Instance
    • Launch TensorBoard in Q Blocks instance
    • Setup Horovod and OpenMPI in Q Blocks Instance
    • Setup AIM for ML experiment tracking
    • Disco Diffusion AI Art on Q Blocks
    • Stable Diffusion Text to Image GPU server on Q Blocks
    • Setup Docker with Nvidia GPU support
    • Enable port forwarding on a Docker container in Q Blocks instance
    • Run production ready lightweight kubernetes using K3s in Q Blocks instance
    • ↗️Upgrade CUDA to v12.2
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  1. Launch a Q Blocks GPU instance

Using Dashboard UI

PreviousLaunch a Q Blocks GPU instanceNextUsing Rest APIs

Last updated 1 year ago

To get started follow the steps below:

  1. Go to Page:

  2. Select a GPU Type:

    1. Different GPUs carry different number of processing cores and memory.

    2. Based on your ML model’s size and number of parameters, you can choose a specific GPU type

  3. Select required data storage:

    1. Q Blocks instances offer fast IO in GPU instances with NVMe/SSD storage access for best performance

  4. Choose an AI Framework Image:

    1. Images help you pre-configure your instance with AI frameworks such as TensorFlow, PyTorch or Keras

    2. They also come with out-of-the-box support for CUDA and GPU drivers.

    3. If you don't a specific framework driven environment then choose base Ubuntu Image.

    4. All these environments offer superuser (sudo su) access with support for installation and management of python pip packages, conda environments etc. You may consider it as a linux based GPU instance which can be modified as per your software needs.

Once the configuration is selected, click on “Create Instance”.

✅ The GPU powered computing instance should be accessible in 1 - 5 minutes.

Checkout this video for quick walkthrough:

We hope to see you make something wonderful with Q Blocks GPU instances.

Technical support:

For any query or issues in getting started, reach us out at for quick resolution.

💻
support@qblocks.cloud
Create Instance