Instructions to use 0xJustin/Dungeons-and-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 0xJustin/Dungeons-and-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("0xJustin/Dungeons-and-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
added license and tag
Browse files
README.md
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See the training dataset here for a list of races: https://huggingface.co/datasets/0xJustin/Dungeons-and-Diffusion
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Model16000 is trained used `D&D character` as the class prompt, and for whatever reason it ~ seems ~ to work better for centaurs and aarakocra
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license: creativeml-openrail-m
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tags:
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- text-to-image
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See the training dataset here for a list of races: https://huggingface.co/datasets/0xJustin/Dungeons-and-Diffusion
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Model16000 is trained used `D&D character` as the class prompt, and for whatever reason it ~ seems ~ to work better for centaurs and aarakocra
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