Instructions to use w3ss/sdxl-lightning-4step-controlnet-coreml-6bits-compiled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use w3ss/sdxl-lightning-4step-controlnet-coreml-6bits-compiled with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("w3ss/sdxl-lightning-4step-controlnet-coreml-6bits-compiled") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "StableDiffusionXLPipeline", | |
| "_diffusers_version": "0.19.0.dev0", | |
| "force_zeros_for_empty_prompt": true, | |
| "add_watermarker": null, | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "text_encoder_2": [ | |
| "transformers", | |
| "CLIPTextModelWithProjection" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "tokenizer_2": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae_encoder": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ], | |
| "vae_decoder": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |