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:
- 27545102a306886af4f837cc80bdd5ad651d371f3a6517864af8b94062b8a643
- Size of remote file:
- 6.59 MB
- SHA256:
- b7db9046c9cd08ef598b99bac3ba0cf1d97554ef0f83b3a0421b52409e23db60
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