Instructions to use nousr/sd-1-5-mse-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nousr/sd-1-5-mse-vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nousr/sd-1-5-mse-vae", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
This repo swaps out the original vae in stable diffusion v1.5 for the new MSE vae found at https://huggingface.co/stabilityai/sd-vae-ft-mse-original.
The results seem very minimal, perhaps i'm improperly swapping the decoder weights...
This is mostly for those curious, so break stuff, try it out, see what works, etc...
NOTE: usage of this model implies accpetance of stable diffusion's CreativeML Open RAIL-M license
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