FLock
Developer GuideGithub
  • What is FLock
    • Introduction to FLock.io
    • The Centralisation Problem
    • Architectural Breakdown
      • System Design
      • Blockchain Layer
      • AI Layer
  • ❤️‍🔥FLock Products
    • AI Arena
      • Participants
      • Quickstart
        • Pre-requisites
          • WSL installation
        • Delegator Guide
        • Training Node Guide
        • Validator Guide
      • Task Lifecycle Deep-dive
      • Smart Contracts Deep-dive
    • FL Alliance
      • Participants
      • Components
      • Task Lifecycle Deep-dive
        • 1. Staking and Role Assignment
        • 2. FL Training
        • 3. FL Aggregation and Evaluation
        • 4. Rewards
      • Smart Contracts Deep-dive
      • FL Client
        • Pre-Requsites
        • Steps to Quickstart
      • FLocKit
    • AI Marketplace
      • Quickstart
        • Getting started Manual creation
        • Guideline Manual
        • Model API guide
        • Tutorials
          • Create a discord bot with Model API
          • Farcaster Frames with Model API
      • Participants
      • Deep-dive
        • Function breakdown
        • RAG
        • Contribution Mechanism
        • Roadmap
    • 2025 Roadmap
  • 💰FLOCK TOKENOMICS
    • Overview
      • Incentivising open source model development
      • Security
    • Token Utility
      • Supply
      • Demand
    • Network Participation
      • AI Arena
        • Task Creator
        • Data Provider
        • Training Node
        • Validator
        • Delegator
        • Delegation Pool Rewards Explainer
      • FL Alliance
        • Task Creator
        • FL Nodes
      • AI Marketplace
        • Model Host
    • Token Allocations
    • Airdrop
    • Contract Details
  • 💻FLock Use-Cases
    • AI-assisted Coding - FLock x Aptos LLM (outperforms ChatGPT-4o!)
    • AI Assistants - Farcaster GPT, Scroll GPT and many more to come!
    • AI Companions - Professor Grump w/ Akash
    • Web3 Agents - Text2SQL Agent
    • Privacy-preserving Healthcare
  • 📃Resources
    • Litepaper
    • Whitepaper
    • Publications
    • Glossary
    • FAQ
    • Social Media
    • Careers
    • Terms Of Use
    • Privacy Policy
    • FLock.io-Verified Developers
    • FLOCK Token Airdrop Terms and Conditions
Powered by GitBook
On this page
  • Introduction
  • Birds of a Feather: Akash & FLock
  • Running a Flock Validator on Akash Network
  • Stake Flock token and generate an API key
  • Create an Akash account
  • Get AKT token
  • Deployment
  • Create Deployment (Optional)

Was this helpful?

  1. FLock Use-Cases

AI Companions - Professor Grump w/ Akash

Run FLock node on Akash network

PreviousAI Assistants - Farcaster GPT, Scroll GPT and many more to come!NextWeb3 Agents - Text2SQL Agent

Last updated 4 months ago

Was this helpful?

NOTE: This post was originally published on the .

Introduction

Developing truly open and decentralised AI is one of society’s most critical challenges. The networks, platforms, and clients we build will help guide this development, from open compute networks like to platforms like FLock that make it easy to train and fine-tune AI models. Integrating these projects simplifies the user experience, enabling greater access that puts AI development directly in the hands of people around the world.

This case study outlines the integration between Akash and FLock that enables users to easily train AI models on decentralised compute. It illustrates how Akash, the first open-source Supercloud, gives AI developers access to the high-performance compute resources needed to train AI models with FLock.io, a platform for decentralised machine learning.

Birds of a Feather: Akash & FLock

As the adage goes, “birds of a feather flock together.” As the decentralized AI movement takes flight, Akash and FLock.io are flying in unison. Akash is an open network that lets users buy and sell computing resources securely and efficiently. FLock.io is an open network that lets users train, validate, and govern AI models democratically and transparently.

Akash is purpose-built for public utility. Compute is available to anyone on the network through Akash’s peer-to-peer marketplace, and the network does not limit the types of tasks or workloads that can be deployed. Similarly, FLock.io is built for and by the community, and the platform does not restrict where models are trained, validated, hosted, and/or deployed.

With a clear alignment on visions for the future and shared values of openness, permissionlessness, and composability, it’s clear to see why Akash and FLock.io are closely aligned.

As you'll see below, FLock has integrated with Akash to create 1-click templates that make it easy to run FLock.io nodes on the Akash Supercloud.

Running a Flock Validator on Akash Network

Video Tutorial:

Stake Flock token and generate an API key

Create an Akash account

You will need a Keplr or Leap wallet to create an Akash account.

Click “CONNECT WALLET” to connect a Keplr or Leap wallet.

When connected to your Keplr wallet, Akash console would show the USDC and AKT balance in your wallet. Deployment on Akash will consume your USDC or AKT.

Get AKT token

You can buy some AKT from any CEX or DEX below, then you need to transfer your AKT to your Keplr or Leap wallet.

Deployment

Click deploy

Input your Flock API and task ID you have staked FLock token on.

Then change the storage to a minimum of 50Gi in builder page, click create deployment.

You can also use the YML file to create deployment. Add your Flock API Key and the Task ID

Choose a provider who is audited, click accept bid.

Then the Flock validator will run automatically in 10 min.


Create Deployment (Optional)

This section is if you wish to run your custom deployment

Click the “DEPLOY” in the upper left corner, and select “Rent GPUs” to rent a GPU

The GPU on the Akash platform is provided to users through docker containers. So you need to provide the image information of the docker container to be deployed, and the hardware configuration of the container.

Choose the GPU count, vCPU count, RAM size.

You can use flockvalidator/pytorch:2.0.1-py3.10-cuda11.8.0-devel-ubuntu22.04 as your docker image, use 8vCPU, 24GB Memory and 60G storage.

After the container configuration is selected, you will enter the provider selection page. You can see all providers that meet the configuration requirements, and their prices and availability are marked. Select one and proceed.

After deployment, you can enter the "SHELL" tab and use the sh command to configure the environment and run the validator.

For advanced users, you can configure sshd service and login via third-party tools such as mobaxterm, xshell.

Follow the steps 1 and 2 mentioned in our to stake Flock token for a validation task and generate an API.

Go to

Choose Flock validator template from templates page

(Docker image link: )

💻
validator guide
https://console.akash.network/
https://console.akash.network/templates
https://hub.docker.com/repository/docker/z471899214308/llm-loss-validator
Akash Blog
Akash
580B
flock-akash_deployment_template.yaml