Instructions to use Envoid/model9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Envoid/model9 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Envoid/model9", 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
- Draw Things
- DiffusionBee
metadata
tags:
- not-for-all-audiences
license: cc-by-nc-4.0
library_name: diffusers
pipeline_tag: text-to-image
Warning this is a highly unstable and experimental merge stack of which some of the donor models were adult oriented leading to certain unintended consequences on occasion.
For SDXL
Deep fried. Experimental.
