Instructions to use fyp1/sketchToImage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fyp1/sketchToImage with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("fyp1/sketchToImage") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "StableDiffusionXLControlNetPipeline", | |
| "_diffusers_version": "0.32.0.dev0", | |
| "_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "controlnet": [ | |
| "diffusers", | |
| "ControlNetModel" | |
| ], | |
| "feature_extractor": [ | |
| null, | |
| null | |
| ], | |
| "force_zeros_for_empty_prompt": true, | |
| "image_encoder": [ | |
| null, | |
| null | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "text_encoder_2": [ | |
| "transformers", | |
| "CLIPTextModelWithProjection" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "tokenizer_2": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |