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:
- 4c0b8ccd36798ae7cf575198eb8787c574085154abbf6c208efeeb5a4e7f7c6e
- Size of remote file:
- 6.59 MB
- SHA256:
- 856fb9ba6fa837fd0f0309d69275b8b6396829e165f11cc19904553bb7049b9b
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