Instructions to use ModelsLab/obj-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/obj-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/obj-controlnet", 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 diffusion_pytorch_model.bin from ModelsLab/obj-controlnet: direct link, hf CLI and curl.
- Browser
- Download file 5 GB
-
https://huggingface.co/ModelsLab/obj-controlnet/resolve/6a58247c07d6638f22d49bdf7d2b5346a4702935/diffusion_pytorch_model.bin
- Command line
-
hf download hf://ModelsLab/obj-controlnet@6a58247c07d6638f22d49bdf7d2b5346a4702935/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/ModelsLab/obj-controlnet/resolve/6a58247c07d6638f22d49bdf7d2b5346a4702935/diffusion_pytorch_model.bin
5 GB
- Xet hash:
- 53aac605ccdf5ba8dfa070d2cc7e1d8d718727fc7f67f710519653db4dc2d8e9
- Size of remote file:
- 5 GB
- SHA256:
- b17ecb76c0dfd3a60896f1eb1783d248ded411c0f9ca9a610352046e0c435910
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