Text-to-Image
Diffusers
Safetensors
English
StableDiffusionXLPipeline
art
people
diffusion
Cinematic
Photography
Landscape
Interior
Food
Car
Wildlife
Architecture
Instructions to use dreamcomputing/ProtoNaut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dreamcomputing/ProtoNaut with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dreamcomputing/ProtoNaut", torch_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
metadata
language:
- en
license: cc-by-nc-nd-4.0
library_name: diffusers
tags:
- art
- people
- diffusion
- Cinematic
- Photography
- Landscape
- Interior
- Food
- Car
- Wildlife
- Architecture
thumbnail: >-
https://storage.googleapis.com/run-diffusion-public-assets/juggernaut-xi/juggernaut-collage-256.webp
base_model:
- RunDiffusion/Juggernaut-XI-v11
- CalypsoCrunchies99/protovisionXLHighfidelity3d_realease0620dff_vaefix
pipeline_tag: text-to-image