horde-worker-reGen

horde-worker-reGen

The default client software to create images for the AI-Horde

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This repository provides the latest implementation for the AI Horde Worker, allowing users to utilize their graphics card(s) to generate, post-process, or analyze images for others. It offers a platform where users can create images and earn 'kudos' in return, granting priority for their own image generations. The repository includes important details for setup, recommendations for system configurations, instructions for installation on Windows and Linux, basic usage guidelines, and information on updating the AI Horde Worker. Users can also run the worker with multiple GPUs and receive notifications for updates through Discord. Additionally, the repository contains models that are licensed under the CreativeML OpenRAIL License.

README:

This repository allows you to set up a AI Horde Worker to generate, post-process or analyze images for others

If you want the latest information or have questions, come to the #local-workers channel in discord

AI Horde Worker reGen

This repo contains the latest implementation for the AI Horde Worker. This will turn your graphics card(s) into a worker for the AI Horde where you will create images for others. You you will receive in turn earn 'kudos' which will give you priority for your own generations.

Important Info

  • An SSD is strongly recommended especially if you are offering more than one model.
    • If you only have an HDD available to you, you can only offer one model and will have to be able to load 3-8gb off disk within 60 seconds or the worker will not function.
  • Do not set threads higher than 2 unless you have a data-center grade card (48gb+ VRAM)
  • Your memory usage will increase up until the number of queued jobs (queue_size in the config).
    • If you have less than 32gb of system ram, you should should stick to queue_size: 1.
    • If you have less than 16gb of system ram or you experience frequent memory-related crashes:
      • Do not offer SDXL/SD21 models. You can do this by adding ALL SDXL and ALL SD21 to your models_to_skip if you are using the TOP N model load option to automatically remove these heavier models from your offerings.
      • Set allow_post_processing and allow_controlnet to false
      • Set queue_size: 0
  • If you plan on running SDXL, you will need to ensure at least 9 gb of system ram remains free while the worker is running.
  • If you have an 8 gb card, SDXL will only reliably work at max_power values close to 32. 42 was too high for tests on a 2080 in certain cases.

AMD

Please note that AMD cards are not currently well supported, but may be in the future.

Update: AMD now has been shown to have better support but for linux machines only - linux must be installed on the bare metal machine; windows systems, WSL or linux containers still do not work. You can now follow this guide using horde-bridge-rocm.sh and update-runtime-rocm.sh where appropriate.

If you are willing to try with your AMD card, join the discord discussion.

Installing

Please see the prior section before proceeding.

If you haven't already, go to AI Horde and register an account, then store your API key somewhere secure. Treat your API key like a password. You will need it later in these instructions. This will allow your worker to gather kudos for your account.

Windows

Using git (recommended)

Use these instructions if you have installed git for windows.

This option is recommended as it will make keeping your repository up to date much easier.

  1. Open powershell (also referred to as terminal) or cmd from the start menu.
  2. Using cd, navigate to a folder that you want the worker installed in.
    • Note that the folder you are in will create a folder named horde-worker-reGen. This folder should not exist before you run the following commands.
    • If you want it to be installed in C:\horde\, run the following:
      • cd C:\horde
      • (if the horde folder doesn't exist)
        cd C:\
        mkdir horde
        cd C:\horde
    • If you are using cmd and wish to install on a different drive, include the /d option, as so:
      • cd /d G:\horde
  3. Run the following commands within the folder chosen (the folder horde if using the example above)
    git clone https://github.com/Haidra-Org/horde-worker-reGen.git
    cd horde-worker-reGen
  4. Continue with the Basic Usage instructions

Without git

Use these instructions if you do not have git for windows and do not want to install it. These instructions make updating the worker a bit more difficult down the line.

  1. Download the zipped version
  2. Extract it to any folder of your choice
  3. Continue with the Basic Usage instructions

Linux

This assumes you have git installed

Open a bash terminal and run these commands (just copy-paste them all together)

git clone https://github.com/Haidra-Org/horde-worker-reGen.git
cd horde-worker-reGen

Continue with the Basic Usage instructions

Basic Usage

The below instructions refers to horde-bridge or update-runtime. Depending on your OS, append .cmd for windows, or .sh for linux

  • for example, horde-bridge.cmd and update-runtime.cmd for windows

Note: If you have an AMD card you should use horde-bridge-rocm.sh and update-runtime-rocm.sh where appropriate

You can double click the provided script files below from a file explorer or run it from a terminal like bash, cmd depending on your OS. The latter option will allow you to see errors in case of a crash, so it's recommended.

Configure

  1. Make a copy of bridgeData_template.yaml to bridgeData.yaml
  2. Edit bridgeData.yaml and follow the instructions within to fill in your details.

Suggested settings

Models are loaded as needed and just-in-time. You can offer as many models as you want provided you have an SSD, at least 32gb of ram, and at least 8gb of VRAM (see Important Info. Workers with HDDs are not recommended at this time but those with HDDs should run exactly 1 model. A typical SD1.5 model is around 2gb each, while a typical SDXL model is around 7gb each. Offering all models is currently around 700gb total and we commit to keeping that number below 1TB with any future changes.

Note: We suggest you disable any 'sleep' or reduced power modes for your system while the worker is running.

  • If you have a 24gb+ vram card:

    - safety_on_gpu: true
    - high_memory_mode: true
    - high_performance_mode: true
    - post_process_job_overlap: true
    - unload_models_from_vram_often: false
    - max_threads: 1 # If you have Flux/Cascade loaded, otherwise 2 max
    - queue_size: 2 # You can set to 3 if you have 64GB or more of RAM
    - max_batch: 8 # or higher
    
  • If you have a 12gb - 16gb card:

    - safety_on_gpu: true # Consider setting to `false` if offering Cascade or Flux
    - high_memory_mode: true
    - moderate_performance_mode: true
    - unload_models_from_vram_often: false
    - max_threads: 1
    - max_batch: 4 # or higher
    
  • If you have an 8gb-10gb vram card:

    • - queue_size: 1 # max **or** only offer flux
      - safety_on_gpu: false
      - max_threads: 1
      - max_power: 32 # no higher than 32
      - max_batch: 4 # no higher than 4
      - allow_post_processing: false # If offering SDXL or Flux, otherwise you may set to true
      - allow_sdxl_controlnet: false
      
    • Be sure to shut every single VRAM consuming application you can and do not use the computer with the worker running for any purpose.
  • Workers which have low end cards or have low performance for other reasons:

    • - extra_slow_worker: true
      • gives you considerably more time to finish job, but requests will not go to your worker unless the requester opts-in (even anon users do not use extra_slow_workers by default). You should only consider using this if you have historically had less than 0.3 MPS/S or less than 3000 kudos/hr consistently and you are sure the worker is otherwise configured correctly.
    • - limit_max_steps: true
      • reduces the maximum total number of steps in a single job you will receive based on the model baseline.
    • - preload_timeout: 120
      • gives you more time to load models off disk. Note: Abusing this value can lead to a major loss of kudos and may also lead to maintainance mode, even with extra_slow_worker: true.

Starting/stopping

Starting the worker

  1. The first time you install, or when updates are required, see Updating for instructions.

  2. Depending on the type of worker:

    • 'Dreamer' worker (image generation): run horde-bridge.
      • Warning: This requires a powerful GPU. You will need a GPU with at least 6GB VRAM and 16GB+ of system RAM.
    • 'Alchemy' worker (upscaling, interrogation, etc) is not current supported and will come in a future version of reGen.

Stopping the worker

  • In the terminal in which it's running, press Ctrl+C together.
  • The worker will finish the current jobs before exiting.

Running with multiple GPUs

In the future you will not need to run multiple worker instances

To use multiple GPUs each has to start their own instance. For linux, you just need to limit the run to a specific card:

CUDA_VISIBLE_DEVICES=0 ./horde-bridge.sh -n "My awesome instance #1"
CUDA_VISIBLE_DEVICES=1 ./horde-bridge.sh -n "My awesome instance #2"

etc

Be warned that you will need a very high (32-64gb+) amount of system ram depending on your settings. queue_size and max_threads increases the amount of ram required per worker substantially.

Updating

The AI Horde workers are under constant improvement. You can follow progress in our discord and get notifications about updates there. If you are interested in receiving notifications for worker updates or betas, go to the #get-roles channel and get the appropriate role(s).

To update:

  1. Shut down your worker by pressing ctrl+c once and waiting for the worker to stop.

  2. Update this repo using the appropriate method:

    git method

    Use this approach if you cloned the original repository using git clone

    1. Open a or bash, cmd, or powershell terminal depending on your OS
    2. Navigate to the folder you have the AI Horde Worker repository installed if you're not already there.
    3. run git pull

    zip method

    Use this approach if you downloaded the git repository as a zip file and extracted it somewhere.

    1. delete the horde_worker_regen/ directory from your folder
    2. Download the repository from github as a zip file
    3. Extract its contents into the same the folder you have the AI Horde Worker repository installed, overwriting any existing files
  3. Run the update-runtime script for your OS. This will update all dependencies if required.

    • Some updates may not require this and the update notification will tell you if this is the case.
    • When in doubt, you should run it anyway.
    • Advanced users: If you do not want to use mamba or you are comfortable with python/venvs, see README_advanced.md.
  4. Continue with Starting/stopping instructions above

Custom Models

You can host your own image models on the horde which are not available in our model reference, but this process is a bit more complex.

To start with, you need to manually request the customizer role from then horde team. You can ask for it in the discord channel. This is a manually assigned role to prevent abuse of this feature.

Once you have the customizer role, you need to download the model files you want to host. Place them in any location on your system.

Finally, you need to point your worker to their location and provide some information about them. On your bridgeData.yaml simply add lines like the following

custom_models:
  - name: Movable figure model XL
    baseline: stable_diffusion_xl
    filepath: /home/db0/projects/CUSTOM_MODELS/PVCStyleModelMovable_beta25Realistic.safetensors

And then add the same "name" to your models_to_load.

If everything was setup correctly, you should now see a custom_models.json in your worker directory after the worker starts, and the model should be offered by your worker.

Note that:

  • You cannot serve custom models with the same name as any of our regular models
  • The horde doesn't know your model, so it will treat it as a SD 1.5 model for kudos rewards and cannot warn people using the wrong parameters such as clip_skip

Docker

See README_advanced.md.

Model Usage

Many models in this project use the CreativeML OpenRAIL License. Please read the full license here.

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