Instructions to use gabai/mill2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gabai/mill2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("gabai/mill2") prompt = "A cinematic shot of a futuristic cyberpunk city street drenched in neon rain, featuring a glowing holographic M1ll3 sign floating above a crowded marketplace." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 0772fd7c937574c4b59f4458325468d532115a7a6aef76fb466c6880299dcaec
- Size of remote file:
- 1.52 MB
- SHA256:
- 8f590d1af8359968e4b37a37cda06cfea7da574138382e65f0c120b7e979a555
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