55 lines
1.8 KiB
Markdown
55 lines
1.8 KiB
Markdown
## Using
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### 1. Install Anaconda
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Anaconda is the preferred method of installing DeepFaceLab on Linux.
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[Just follow the tutorial](https://docs.conda.io/projects/conda/en/latest/user-guide/install).
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### 2. Install System Dependencies
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You will need FFMpeg, Git, and the most recent NVIDIA driver for your system to use this project.
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If you are here, then you already have everything...
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### 3. Install DeepFaceLab
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Just run it in the terminal.
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Check latest cudnn and cudatoolkit version for your GPU device.
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```bash
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conda create -n deepfacelab -c main python=3.7 cudnn=7.6.5 cudatoolkit=10.1.243
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conda activate deepfacelab
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git clone --depth 1 https://github.com/nagadit/DeepFaceLab_Linux.git
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cd DeepFaceLab_Linux
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git clone --depth 1 https://github.com/iperov/DeepFaceLab.git
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python -m pip install -r ./DeepFaceLab/requirements-cuda.txt
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```
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you can confirm your gpu is working correctly by running the following code and seeing what messages pop up:
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```bash
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python -c "import tensorflow as tf;print(tf.__version__)"
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```
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If the scripts can't seem to access the GPU and you're having issues with cuda version mismatches when running `nvidia-smi`, they can sometimes be remedied by simply running
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```bash
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conda install tensorflow-gpu==2.4.1
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```
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## 4. Download Pretrain (optional)
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Use script 4.1 from the scripts directory.
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Or download manually
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[CelebA](https://github.com/nagadit/DeepFaceLab_Linux/releases/download/1.0/pretrain_CelebA.zip)
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[FFHQ](https://github.com/nagadit/DeepFaceLab_Linux/releases/download/1.0/pretrain_FFHQ.zip)
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[Quick96](https://github.com/nagadit/DeepFaceLab_Linux/releases/download/1.0/pretrain_Quick96.zip)
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## 5. Navigate to the scripts directory and begin using DeepFaceLab_Linux ᗡ:
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Run all scripts with BASH shell
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```bash
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bash 1_clear_workspace.sh
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```
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etc
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