A streamlined setup for developing on high-performance hardware.
- Authentication credentials set via secrets for:
- Code server authentication
- Jupyterlab authentication
- Hugging Face and CivitAI tokens for model access (mandatory).
Ensure that the required environment variables and secrets are correctly set before running the pod. See below for options.
- Runpod.io
- GPU
Component | Version |
---|---|
OS | Ubuntu 22.04 x86_64 |
Python | 3.11.x |
PyTorch | 2.8.0 |
NVCC | 12.9 |
Triton | 3.x |
docker pull ls250824/run-pytorch-cuda-develop:<version>
Service | Port |
---|---|
Code Server | 9000 (HTTP) |
Jupyterlab | 8888 (HTTP) |
SSH/SCP | 22 (TCP) |
Gradio | 7860 (HTTP) |
Token | Environment Variable |
---|---|
Civitai | CIVITAI_TOKEN |
Huggingface | HF_TOKEN |
Code Server | PASSWORD |
Jupyterlab | JUPYTERLAB_PASS |
7z a output.7z /workspace/output/
7z x x.7z
civitai "<dowload link>" /workspace
huggingface-cli download model model_name.safetensors --local-dir /workspace
huggingface-cli upload model /workspace/model.safetensors
nvtop
htop
mc
nano
tmux
c++
nvcc
python
pip
ncdu
unzip
Option | Description | Default |
---|---|---|
--username |
Docker Hub username | Current user |
--tag |
Tag to use for the image | Today's date |
--latest |
If specified, also tags and pushes as latest |
Not enabled by default |
Run the following command to clone the repository and build the image:
git clone https://github.com/jalberty2018/run-pytorch-cuda-develop.git
cp run-pytorch-cuda-develop/build-docker.py ..
python3 build-docker.py \
--username=<your_dockerhub_username> \
--tag=<custom_tag> \
run-pytorch-cuda-develop
Note: If you want to push the image with the latest tag, add the --latest flag at the end.