Instructions to use Onocom/Ono-Mixes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Onocom/Ono-Mixes with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Onocom/Ono-Mixes", 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
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| tags: | |
| - safetensors | |
| - diffusers:StableDiffusionPipeline | |
| # just fun little merge projects | |
| ## about Model Merges: | |
| <p> | |
| <b>these are merges I made over the time, mixing everything I like and find</b><br> | |
| Most merges are sorted by what they are from<br> | |
| - 1.5 Fluffyrock<br> | |
| - pony<br> | |
| - noob<be> | |
| I like working on Vpred models and trying to have them Stable and working well. | |
| </p> |