Image-to-Image
Diffusers
Safetensors
StableDiffusionControlNetPipeline
controlnet
stable-diffusion
satellite-imagery
osm
Instructions to use MVRL/VectorSynth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MVRL/VectorSynth with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("MVRL/VectorSynth") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "StableDiffusionControlNetPipeline", | |
| "_diffusers_version": "0.21.0", | |
| "controlnet": [ | |
| "diffusers", | |
| "ControlNetModel" | |
| ], | |
| "feature_extractor": [ | |
| "transformers", | |
| "CLIPImageProcessor" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "DDIMScheduler" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } |