Unfortunately, AMD GPUs #63 and MacOs #35 are not supported, contributions to add support are very welcome.

This is an indicator that the container does not have enough RAM, you need at least 12GB, recommended 16GB.

You might need to adjust the size of the docker virtual machine RAM depending on your OS.

Error response from daemon: dockerfile parse error line 33: unknown instruction: GIT
ERROR: Service 'model' failed to build : Build failed

Update docker to the latest version, and make sure you are using docker compose instead of docker-compose. #16, also, try setting the environment variable DOCKER_BUILDKIT=1

Update docker to the latest version, and see this comment, try setting the environment variable mentioned in the previous point.

use --precision full --no-half. #9

add NVIDIA_DRIVER_CAPABILITIES=compute,utility and NVIDIA_VISIBLE_DEVICES=all to container can resolve this problem #348

Install NVIDIA Container Toolkit and restart the docker service #81

This might be related to the overlay2 storage driver used by docker overlayed on zfs, change to the zfs storage driver #433

Edit the corresponding docker file, and change the SHELL from /bin/bash to //bin/bash #21, note: this is a hack and something in your wsl is messed up.

You can try forcing plain text auth creds storage by removing line with "credStore" from ~/.docker/config.json (in WSL). #56

Set the build/network of the service you are starting to host #114

• Make sure:
  • Windows 10 release >= 2021H2 (required for WSL to see the GPU)
  • WSL2 (check with wsl -l -v)
  • Latest Docker Desktop
• You might need to create a .wslconfig and increase memory, if you have 16GB RAM, set the limit to something around 12GB, #34 #64
• You might also need to force wsl to allow file permissions

You have to use one of AWS's GPU-enabled VMs and their Deep Learning OS images. These have the right divers, the toolkit and all the rest already installed and optimized. #70