Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
Base Model
General purpose
Photorealistic
Anime
Illustration
Cartoon
artificialguybr
s6yx
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yntec/365 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/365 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/365", 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
Commit History
-
Update scheduler/scheduler_config.json
Verified signature2bb3509 -
Update scheduler/scheduler_config.json
Verified signature3af6dd7 -
Update scheduler/scheduler_config.json
Verified signature6a104cd -
Update scheduler/scheduler_config.json
Verified signature0fa86a4 -
Adding `diffusers` weights of this model (#1)
Verified signature- Adding `diffusers` weights of this model (e11c0a2fe244f5e1099d63dbd04a643dbd48abe5)9bfae87