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
Single files
Diffusers supports loading pretrained pipeline (or model) weights stored in a single file, such as a ckpt or safetensors file. These single file types are typically produced from community trained models. There are three classes for loading single file weights:
- [
FromSingleFileMixin] supports loading pretrained pipeline weights stored in a single file, which can either be ackptorsafetensorsfile. - [
FromOriginalVAEMixin] supports loading a pretrained [AutoencoderKL] from pretrained ControlNet weights stored in a single file, which can either be ackptorsafetensorsfile. - [
FromOriginalControlnetMixin] supports loading pretrained ControlNet weights stored in a single file, which can either be ackptorsafetensorsfile.
To learn more about how to load single file weights, see the Load different Stable Diffusion formats loading guide.
FromSingleFileMixin
[[autodoc]] loaders.single_file.FromSingleFileMixin
FromOriginalVAEMixin
[[autodoc]] loaders.autoencoder.FromOriginalVAEMixin
FromOriginalControlnetMixin
[[autodoc]] loaders.controlnet.FromOriginalControlNetMixin