Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Realism
Portrait
Photo
Photorealism
anime
art
artistic
darkstorm2150
ChangeMeNot
stable-diffusion-1.5
stable-diffusion-diffusers
Instructions to use Yntec/ThisIsPromising with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/ThisIsPromising with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/ThisIsPromising", 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:
- 060fb1429212896bb1b0ac1b90a0efe3f88e4e32dbb146514cea0f2cfb8aaac3
- Size of remote file:
- 492 MB
- SHA256:
- fe2f08899334a9d46a5da989e668094dd2cc0c1f986116942979b15af9e76b2d
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