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:
- bf8a7647813b581c1621f0ecce72dfdbe052095243c218ca97274fc8b746b53e
- Size of remote file:
- 3.29 MB
- SHA256:
- 30c5a6434698500e5e70a76af64fb7116f9dd0ce4922a2119ef5117b0e892c1c
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