forcedemolisherroad/deepfacelab

★ 20Audience · generalComplexity · 3/5Setup · moderate

Mindmap

mindmap
  root((deepfacelab build))
    What it does
      Face swap in video
      Batch video processing
      Custom model training
      Video quality improvement
    Model types
      SAEHD
      Quick96
      AMP
    Requirements
      Windows 10 or 11 64-bit
      NVIDIA GPU preferred
      CPU fallback available
    Install
      Download from Telegram
      Run setup as Administrator

mindmap root((deepfacelab build)) What it does Face swap in video Batch video processing Custom model training Video quality improvement Model types SAEHD Quick96 AMP Requirements Windows 10 or 11 64-bit NVIDIA GPU preferred CPU fallback available Install Download from Telegram Run setup as Administrator

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Things people build with this

USE CASE 1

Replace a face in a video clip using a pre-trained model without building from source

USE CASE 2

Train a custom face-swap model on your own footage using the SAEHD or AMP architecture

USE CASE 3

Process an entire video in batch mode rather than swapping frames one at a time

USE CASE 4

Run face-swap on a Windows machine without an NVIDIA GPU using the CPU fallback

Tech stack

PythonCUDANVIDIA

Getting it running

Difficulty · moderate Time to first run · 1h+

Requires downloading from a Telegram link and running setup as Administrator on Windows 10/11, NVIDIA GPU strongly recommended for reasonable training speed.

No license information is provided, this appears to be an unofficial redistribution of the original DeepFaceLab project.

In plain English

This repository distributes a pre-packaged Windows build of DeepFaceLab, a well-known face-swap program. The software takes video footage and replaces one person's face with another using deep learning techniques. According to the README, it runs on Windows 10 and 11 (64-bit) and works best with an NVIDIA graphics card, though a CPU fallback is listed as available. The build advertises several face-swap capabilities: swapping faces in videos, improving output video quality, processing entire videos in batch rather than frame by frame, and training custom models on your own footage. The README lists three model architectures by name (SAEHD, Quick96, and AMP) without explaining what distinguishes them. The claim that this software is "used in 95% of deepfake content worldwide" comes from the README itself and is not independently verifiable. The installation process described is straightforward: download an archive from a Telegram link, extract it, run a setup file as Administrator, and the software launches with all features active. The README also lists several restrictions that have been removed from this build, including subscription requirements and feature gates, which suggests this is not an official release from the original DeepFaceLab project. The README is brief and mostly consists of a feature checklist and install steps. It does not explain how training works, what data you need to collect, or how long the process takes. For anyone unfamiliar with deepfake creation, the actual workflow of gathering source footage, training a model, and applying a face swap would require guidance beyond what this repository provides.

Copy-paste prompts

Prompt 1

I installed the DeepFaceLab Windows build. Walk me through the full workflow: gathering source footage, training a face-swap model, and applying it to a target video.

Prompt 2

What is the difference between the SAEHD, Quick96, and AMP model architectures in DeepFaceLab, and when should I choose each one?

Prompt 3

My DeepFaceLab training is producing blurry output. What settings in the SAEHD model should I adjust to improve sharpness and reduce artifacts?

Prompt 4

How do I set up DeepFaceLab to use my NVIDIA GPU for training instead of the CPU fallback, and how can I check that the GPU is being used?

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