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", 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
- Xet hash:
- 46bf0d6019a8de548a0f20ec2634e84e5489ffb89afc8421b17f95039822becf
- Size of remote file:
- 2.73 GB
- SHA256:
- 737ad6a44990098484d628eea2f7cebba3bbccc97b3aa75b6f6bcd5c8821e7df
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