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Docker image to play TensorRT technology with AUTOMATIC1111's web ui. Docker image: kopyl/a1111-tensorrt

Features:

  • Speed of image generation is ≈75it/s for Stable Diffusion 1.5
  • You can run it from Runpod. Video tutorial

Requirements for Runpod:

  • Expose ports: 8888, 3000
  • Reserve disk space: 100 GB for contaier volume
  • Configure right GPU: NVIDIA RTX 4090

Metadata:

  • NVIDIA driver: 535.104.12
  • CUDA driver: 11.8

When this can be useful:

  • When you reuse one or some set of Stable Diffusion models a lot (not suitable for one-time generation)
  • When you generate a lo of images for your videos (it's suitable cause when you save 1± second per image, it's a lot of time for like 2-3 minutes video)

Are there any other ways to speed up image generation?

  • Convert SD model to fp16
  • Use Oneflow (it's tricky, cause without any modification of the source code of the library you're going to get a huge cold start, so the speed evens out and also you can't use it with A1111, since it's Diffusers-like tech)

How to contribute:

  • You can freeze current commit of repositories (A1111 and TensorRT extension)
  • You can add a serverless Dockerfile and a handler for Runpod