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

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Basic Instance functionality:
Machine learning tooling setup:
Supported by Pro Instances:
Docker setup:

🤔Q Blocks How To Guide

PreviousIAM: Share access with team NextCreate a new user

Last updated 1 year ago

Q Blocks is a decentralized computing infrastructure platform designed to serve ML workloads at scale.

To enable full feature utilization, we provide you a quick How-To Guide.

The guide contains documentation to help you quickly get started with functionalities that Q Blocks instances offer out of the box:

Basic Instance functionality:

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

Upgrade Instance CUDA to version 12.2

Machine learning tooling setup:

Launch TensorBoard in Q Blocks instance

Supported by Pro Instances:

Docker setup:

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