Instructions to use bodam/model_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bodam/model_lora 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_lora") prompt = "a s3f chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 239682d7aa8ce22647d4d634b840c32f71927cffd801d68ee8f4c2250790ad6f
- Size of remote file:
- 6.59 MB
- SHA256:
- ab32011a635d63a235233a66fadbc088912051b80252044817dea270f74a8d88
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