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:
- eb2f49aab4a4d2c1ba6cd66bc5fdb171e6299dc326512ff40b737aadafee619f
- Size of remote file:
- 195 MB
- SHA256:
- 315b696bad48bd80820a880f9815d90c35c3310ceec70b8fcc871ed510ea7379
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