Instructions to use bodam/model_lora2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bodam/model_lora2 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_lora2") prompt = "a s3f chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7980da8ab649afac2fbe4cbd619f3117b8484e72e6a98794d0c58a410d5c91f3
- Size of remote file:
- 6.59 MB
- SHA256:
- 03101df2ce80609d853e1cd78edb09eb853225ba0a58b6f597a1c249c9083594
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