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", 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
- Xet hash:
- faddaf4c28264a23fdb39876b81fe5769dfa93dbf05e055393b9ad6e9fe03510
- Size of remote file:
- 246 MB
- SHA256:
- c5bd3587ce51860f3e7560d540399053fba61c1ab7a8737f6be8ea9311d651e2
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