Instructions to use eristotelian/milora1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eristotelian/milora1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("eristotelian/milora1") prompt = "milora" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 533048e01527db1452d41726416f8e540879f434a96ed864f280479bdae8aace
- Size of remote file:
- 474 kB
- SHA256:
- 1e0a5b8bbe2a54572714c6418df7a9dfcc420a10fd1a29b5a237b81f82cc6ec9
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