Image-to-Image
Diffusers
StableDiffusionControlNetPipeline
stable-diffusion
stable-diffusion-diffusers
controlnet
jax-diffusers-event
Instructions to use vllab/controlnet-hands with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vllab/controlnet-hands with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("vllab/controlnet-hands") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "AutoencoderKL", | |
| "_diffusers_version": "0.17.0.dev0", | |
| "_name_or_path": "/root/.cache/huggingface/hub/models--runwayml--stable-diffusion-v1-5/snapshots/aa9ba505e1973ae5cd05f5aedd345178f52f8e6a/vae", | |
| "act_fn": "silu", | |
| "block_out_channels": [ | |
| 128, | |
| 256, | |
| 512, | |
| 512 | |
| ], | |
| "down_block_types": [ | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D" | |
| ], | |
| "in_channels": 3, | |
| "latent_channels": 4, | |
| "layers_per_block": 2, | |
| "norm_num_groups": 32, | |
| "out_channels": 3, | |
| "sample_size": 512, | |
| "scaling_factor": 0.18215, | |
| "up_block_types": [ | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D", | |
| "UpDecoderBlock2D" | |
| ] | |
| } | |