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Docker image with Jupyter, Pytorch and CUDA GPUs supports.

Dockerfile and Docker Compose setup for ComfyUI - Works on Linux or Windows with NVIDIA GPUs

Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready and real time inference.

Docker image: Keras in Docker for reproducible deep learning on CPU or GPU

Open source Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in PyTorch, OpenCV (compiled for GPU), TensorFlow 2 for GPU, PyG and NVIDIA RAPIDS

Easier than K8s to lift and lower the gpu number of docker container and scale capacity size of volume.

Production-ready UVR5 CLI & Docker image. Run SOTA separation models (Roformer, SCNet, MDX, Demucs, VR Architecture) on headless GPU servers without dependency hell.

This is a Docker container that replicates the Google colab(https://colab.research.google.com/) runtime environment, used to quickly launch a container that is almost identical to the colab environment, allowing for colab to connect to local GPUs for computation.

Run llama.cpp in a GPU accelerated Docker container