Instructions to use nitrosocke/redshift-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/redshift-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nitrosocke/redshift-diffusion", 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
Help request: embed training for redshift model
#24
by SamTyurenkov - opened
Hi there, thanks for the awesome model.
Im trying to train an embed on custom subject. I want to achieve photorealistic tiger tank, but so far it still comes out with some artefacts:
This last attempt was a training with based on single angle of tiger tank on different backgrounds. I used keywords describing background in filenames, selected a default subject filewords template, 30 vectors per token and "photorealistic tiger tank" init text. Trained for 5000 steps.
Most artefacts appear on the gun + it cant add the subject into background as cool as in prompts without embed.
Any advice is appreciated, im also willing to purchase a paid consultation if possible.
Thank you again!



