Instructions to use na1taneja2821/diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use na1taneja2821/diffusers 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("na1taneja2821/diffusers") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
PEFT
Diffusers supports loading adapters such as LoRA with the PEFT library with the [~loaders.peft.PeftAdapterMixin] class. This allows modeling classes in Diffusers like [UNet2DConditionModel] to load an adapter.
Refer to the Inference with PEFT tutorial for an overview of how to use PEFT in Diffusers for inference.
PeftAdapterMixin
[[autodoc]] loaders.peft.PeftAdapterMixin