Instructions to use flax/Stable_Diffusion_PaperCut_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flax/Stable_Diffusion_PaperCut_Model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("flax/Stable_Diffusion_PaperCut_Model", 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 Settings
- Draw Things
- DiffusionBee
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Download README.md from flax/Stable_Diffusion_PaperCut_Model: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
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https://huggingface.co/flax/Stable_Diffusion_PaperCut_Model/resolve/961191bf14c918dca9af8ad608facb17c56effee/README.md
- Command line
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hf download hf://flax/Stable_Diffusion_PaperCut_Model@961191bf14c918dca9af8ad608facb17c56effee/README.md
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curl -L -o README.md https://huggingface.co/flax/Stable_Diffusion_PaperCut_Model/resolve/961191bf14c918dca9af8ad608facb17c56effee/README.md
125 Bytes
metadata
license: openrail
library_name: diffusers
tags:
- TPU
- JAX
- Flax
- stable-diffusion
- text-to-image
language:
- en