Instructions to use Shirmil/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shirmil/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("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Shirmil/lora_model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 737d55f3f42f0603fe4c33f411fc4df9bce51cd7c5d154b8973f4323834ffc0e
- Size of remote file:
- 1 kB
- SHA256:
- d3232bfa8f95c36e916cac486d0f97757ae0801450231d4327bab62990c7f962
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