Instructions to use Polycruz9/mj-mix2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Polycruz9/mj-mix2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Polycruz9/mj-mix2") prompt = "MJ v6, Portrait photography of a woman in a red dress, in the style of unsplash photography, street photography, dark green background --ar 47:64 --v 6.0 --style raw" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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