Instructions to use bodam/model_lora5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bodam/model_lora5 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("bodam/model_lora5") prompt = "a olis chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a17add4270e876c4cda02c5fa487a7c566f600f9fd45ea09b9015dedeb5b2afc
- Size of remote file:
- 6.59 MB
- SHA256:
- 796d5f894b714f8b214c3278a01108168445925894ac9eaea738739188b19a60
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