Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Base Model
General purpose
Photorealistic
Anime
Art
Sexy
Pinups
Girls
Sygil
iamxenos
RIXYN
Barons
artificialguybr
stable-diffusion
stable-diffusion-1.5
stable-diffusion-diffusers
Instructions to use Yntec/Imaginary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Imaginary 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/Imaginary", 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:
- 535339899dce04ca0a81cf6a0eb3e40ea55eb3edced32cc071029ab758dbee6c
- Size of remote file:
- 3.44 GB
- SHA256:
- 63416091f800656b9fa30850ac82299a0e88309cb63e122d05bffa01b1d8c970
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.