Instructions to use EnD-Diffusers/Duskfall_Portraits_Epic_Train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use EnD-Diffusers/Duskfall_Portraits_Epic_Train with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("EnD-Diffusers/Duskfall_Portraits_Epic_Train", 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
Duskfall-Alter-Test-V2 Dreambooth model trained by Duskfallcrew with TheLastBen's fast-DreamBooth notebook
Test the concept via A1111 Colab fast-Colab-A1111
If you want to donate towards costs and don't want to subscribe:
https://ko-fi.com/DUSKFALLcrew
Sample Images Are available here
Text files are in the file here: https://huggingface.co/Duskfallcrew/Duskfall_Portraits_Epic_Train/tree/main/Epic%20Train%20Samples
This was trained on Epic Diffusion because for some reason it wasn't letting me use Never Ending Dream.
dskfll SHOULD be the token
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