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
File size: 442 Bytes
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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> |