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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3e691841c63ff3f8d97a2f50a19872b7bb052ddd527213b12beaf814f14a21bf
- Size of remote file:
- 1.39 GB
- SHA256:
- 30b466dbbac35c5c63d0fc1893c17433f0d367886c1081d4a699ce728ed013af
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