Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
Base Model
Realism
Photorealistic
Person
Portrait
residentchiefnz
PromptSharingSamaritan
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/beLIEve with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/beLIEve 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/beLIEve", 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:
- a848a47ab849b3da7004d3c5a53d6669f9e6cf7a1b61b432ccd09a2741b22195
- Size of remote file:
- 3.44 GB
- SHA256:
- 53e5ac938a6c6af3f57919d8bfa3c22096be99d7004de93a45d989fff759105e
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