Instructions to use eagle13gy/path_to_lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use eagle13gy/path_to_lora_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("eagle13gy/path_to_lora_model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9a90ace65bbc47602ab046a3df8a6bf9059154483972a88cf9e200af33e099ba
- Size of remote file:
- 6.59 MB
- SHA256:
- 2694525b3fd2cfa917b06d740ba7418e9a539ae61cc6e5e269366eb808855d63
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