Instructions to use alimama-creative/SD3-Controlnet-Inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alimama-creative/SD3-Controlnet-Inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alimama-creative/SD3-Controlnet-Inpainting", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download config.json from alimama-creative/SD3-Controlnet-Inpainting: direct link, hf CLI and curl.
- Browser
- Download file 442 Bytes
-
https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/resolve/main/config.json
- Command line
-
hf download hf://alimama-creative/SD3-Controlnet-Inpainting/config.json
-
curl -L -o config.json https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/resolve/main/config.json
442 Bytes
| { | |
| "_class_name": "SD3ControlNetModel", | |
| "_diffusers_version": "0.29.2", | |
| "_name_or_path": "./model_hub_tmp_0/.", | |
| "attention_head_dim": 64, | |
| "caption_projection_dim": 1536, | |
| "in_channels": 16, | |
| "joint_attention_dim": 4096, | |
| "num_attention_heads": 24, | |
| "num_layers": 23, | |
| "out_channels": 16, | |
| "patch_size": 2, | |
| "pooled_projection_dim": 2048, | |
| "pos_embed_max_size": 192, | |
| "sample_size": 128, | |
| "extra_conditioning_channels": 1 | |
| } | |