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", 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
IP-Adapter
IP-Adapter is a lightweight adapter that enables prompting a diffusion model with an image. This method decouples the cross-attention layers of the image and text features. The image features are generated from an image encoder.
Learn how to load an IP-Adapter checkpoint and image in the IP-Adapter loading guide, and you can see how to use it in the usage guide.
IPAdapterMixin
[[autodoc]] loaders.ip_adapter.IPAdapterMixin
IPAdapterMaskProcessor
[[autodoc]] image_processor.IPAdapterMaskProcessor