Instructions to use InstantX/SD3-Controlnet-Pose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/SD3-Controlnet-Pose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/SD3-Controlnet-Pose", 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
Download config.json from InstantX/SD3-Controlnet-Pose: direct link, hf CLI and curl.
- Browser
- Download file 397 Bytes
-
https://huggingface.co/InstantX/SD3-Controlnet-Pose/resolve/1c550dbb8f7b35098ae7c91f498d1a753c9f49ea/config.json
- Command line
-
hf download hf://InstantX/SD3-Controlnet-Pose@1c550dbb8f7b35098ae7c91f498d1a753c9f49ea/config.json
-
curl -L -o config.json https://huggingface.co/InstantX/SD3-Controlnet-Pose/resolve/1c550dbb8f7b35098ae7c91f498d1a753c9f49ea/config.json
397 Bytes
| { | |
| "_class_name": "ControlNetSD3Model", | |
| "_diffusers_version": "0.29.0.dev0", | |
| "_name_or_path": "/path/", | |
| "attention_head_dim": 64, | |
| "caption_projection_dim": 1536, | |
| "in_channels": 16, | |
| "joint_attention_dim": 4096, | |
| "num_attention_heads": 24, | |
| "num_layers": 6, | |
| "out_channels": 16, | |
| "patch_size": 2, | |
| "pooled_projection_dim": 2048, | |
| "pos_embed_max_size": 192, | |
| "sample_size": 128 | |
| } | |