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gpu-dev

A docker image environment for LLM development on GPUs (Nvidia), useful with gcube or vastai.

Include torch, transformers, unsloth, flash-attn, axolotl.

Use port 8000 for jupyter notebook.

Usage

Cuda 12.6

docker pull ghcr.io/deveworld/gpu-dev:cuda-12.6

Cuda 12.8 (for 50XX)

docker pull ghcr.io/deveworld/gpu-dev:cuda-12.8

Make Docker Image

Need >= 210GB RAM

Clone

git clone https://github.com/deveworld/gpu-dev

Build

sudo docker build -t ghcr.io/deveworld/gpu-dev:latest -t ghcr.io/deveworld/gpu-dev:cuda-12.6 . -f 12.6/Dockerfile
sudo docker build -t ghcr.io/deveworld/gpu-dev:cuda-12.8 . -f 12.8/Dockerfile

Login

sudo docker login --username {username} --password-stdin

Push

sudo docker push ghcr.io/deveworld/gpu-dev --all-tags

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A docker image environment for LLM development on GPUs (Nvidia), useful with gcube or vastai.

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