Making DeepFakes using DeekFaceLab - Github Code and Implementation Guide

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  • Aug 15, 2016
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    අදාල නෑනේ
    Recommended hardware configuration:

    - modern 8-32 core CPU supporting AVX and SSE instructions

    - 32GB of RAM for single GPU configuration, 64GB+ for 2+ GPUs
    (in general best to have more RAM than total VRAM of all gpus, so 2x4090 = 2x24GB = 48GB, considering modern kits use 16/32GB sticks that would be 64GB of RAM)

    - 1000 series or higher Nvidia GPU with 8GB VRAM minimum
    (good for up to 256 resolutions models, for 256-320 11-12GB required, for 320+ 16-24GB GPUs required)

    - plenty of fast SSD storage space and pagefile set to 4x of RAM size minimum if you have more RAM than total of all GPU's VRAM if you plan on using all GPUs at the same time
    (or 5x to be sure if you have less, say 3x3060 = 36GB on 32GB system).
    You may be able to get away with less or auto settings if you have single gpu, for multiple GPU setups I recommend 5x just to be safe.

    Cooling - you will need to make sure your hardware is cooled adequately (check temps of your CPU and GPU during heavy use, if anything is above 85 degrees consider changign your CPU cooler and replacing thermal paste on both CPU and GPU if you know how to do it).

    Power supply - training often can take days and a weak, no-name PSU may fail on you, possibly damaging other hardware, make sure your PSU is from a good brand and isn't an entry level/budget unit, also make sure it meets power requirements of your configuration, use the PSU power calculator below to check if your unit is good enough, if not upgrade it.
     
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    BenMacTavish

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  • May 3, 2021
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    Can be implemented via colab

    Resources in Colab are prioritized for interactive use cases. We prohibit actions associated with bulk compute, actions that negatively impact others, as well as actions associated with bypassing our policies. The following are disallowed from Colab runtimes:
    • file hosting, media serving, or other web service offerings not related to interactive compute with Colab
    • downloading torrents or engaging in peer-to-peer file-sharing
    • using a remote desktop or SSH
    • connecting to remote proxies
    • mining cryptocurrency
    • running denial-of-service attacks
    • password cracking
    • using multiple accounts to work around access or resource usage restrictions
    • creating deepfakes
    source: https://research.google.com/colaboratory/faq.html#limitations-and-restrictions
     

    BernieSanders

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  • Jun 11, 2016
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    Resources in Colab are prioritized for interactive use cases. We prohibit actions associated with bulk compute, actions that negatively impact others, as well as actions associated with bypassing our policies. The following are disallowed from Colab runtimes:
    • file hosting, media serving, or other web service offerings not related to interactive compute with Colab
    • downloading torrents or engaging in peer-to-peer file-sharing
    • using a remote desktop or SSH
    • connecting to remote proxies
    • mining cryptocurrency
    • running denial-of-service attacks
    • password cracking
    • using multiple accounts to work around access or resource usage restrictions
    • creating deepfakes
    source: https://research.google.com/colaboratory/faq.html#limitations-and-restrictions
    You have to get the paid version of colab. Free version doesn’t let you train deepfakes
     
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