Instructions to use p1atdev/plat-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use p1atdev/plat-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("p1atdev/plat-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
doc: add sample image
Browse files
README.md
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license: creativeml-openrail-m
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license: creativeml-openrail-m
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# Plat Diffusion v0.1
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Plat Diffusion is a fine-tuned model based on [8528-diffusion](https://huggingface.co/852wa/8528-diffusion) with images generated with niji・journey and NovelAI.
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```
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1girl, body made of glass fragments, refraction, blue hour
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```
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