Instructions to use nitrosocke/Nitro-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Nitro-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("nitrosocke/Nitro-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 Settings
- Draw Things
- DiffusionBee
Commit History
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Add Diffusers weights
Add Diffusers weights converted from checkpoint `nitroDiffusion-v1.ckpt` in revision f23b33297e300f08b1bc1bb645e2b76de2c555a0e39f3cf
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add gradio demo link (#7)
- add gradio demo link (2fda2a98677a1f7a057caf77e9aa2a8095bdeda8) Co-authored-by: Ahsen Khaliq <akhaliq@users.noreply.huggingface.co>f23b332
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Update README tags to detect properly that this is a `diffusers` model to enable the free widget inference. (#3)
- Update README tags to detect properly that this is a `diffusers` model to enable the free widget inference. (ea92155c0dbdb123979ecba4a4e4fdf9ed68e7b4) Co-authored-by: Nicolas Patry <Narsil@users.noreply.huggingface.co>9552844 -
Add a diffusers checkpoint (#4)
- Add a diffusers checkpoint (0ea24749bb659700f97e8a99639ba5dab3a74c61) Co-authored-by: Anton Lozhkov <anton-l@users.noreply.huggingface.co>516c17f -
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