Instructions to use EPFL-IVRL/sd2.1-base-colorednoiseDFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EPFL-IVRL/sd2.1-base-colorednoiseDFT with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EPFL-IVRL/sd2.1-base-colorednoiseDFT", 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
You need to agree to share your contact information to access this model
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
By clicking "Agree", you acknowledge that this model is released solely for academic research purposes. It is initialized from Stable Diffusion v2.1 base (CreativeML Open RAIL++-M License) and further trained on a subset of the Re-LAION-5B (research-safe) dataset. You agree to review and comply with the terms and licenses of both the pretrained model and training dataset, and you bear responsibility for any use of this model.
Log in or Sign Up to review the conditions and access this model content.
Gated model You can list files but not access them
Preview of files found in this repository