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:
- d21ce9fa27e8a8e9479c2de9eb48637b6a985bf4a23023002a543c545c6bb87b
- Size of remote file:
- 195 MB
- SHA256:
- a3a7245910d9bbaa53a7de80f4188d5343e7bdf9d776c67c341da07607cafac5
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