Instructions to use Duskfallcrew/duskfalltest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Duskfallcrew/duskfalltest with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Duskfallcrew/duskfalltest", dtype=torch.bfloat16, device_map="cuda") prompt = "duskypie" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Commit ·
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Parent(s): c8d58ad
Update README.md
Browse filesFinal nail in the coffin, xD asking for people to be nice. HMPH!
Anyways, was just cleaning up the public face image wanna make the mode public to test it more
README.md
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@@ -32,6 +32,8 @@ Trained using the MultiModel Dreambooth App, sitting on a friday afternoon doing
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Please DO NOT re-upload the sample pictures that it was trained on, except in the instance you are inspired to use img2img..
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In which we dutifully ask you to spam the community section with your outputs.
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Figured might as well make this public for giggles, it's not a perfect model. Am cleaning up some of the concept folder as some of the concepts its trained on are not ones we want in the public eye.
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Model is under the creativeml-openrail-m, and of course - trained on 99% lazy afternoons.
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Please DO NOT re-upload the sample pictures that it was trained on, except in the instance you are inspired to use img2img..
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In which we dutifully ask you to spam the community section with your outputs.
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This would hopefully include anything that is in the concept folder, though it'd be nice if you do use anything of ours in your larger data set to maybe be nice and credit? pretty plz?
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Figured might as well make this public for giggles, it's not a perfect model. Am cleaning up some of the concept folder as some of the concepts its trained on are not ones we want in the public eye.
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Model is under the creativeml-openrail-m, and of course - trained on 99% lazy afternoons.
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