Instructions to use blueskyfff/sd-controlnet-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- paddlenlp
How to use blueskyfff/sd-controlnet-depth with paddlenlp:
# ⚠️ Type of model unknown from paddlenlp.transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("blueskyfff/sd-controlnet-depth", from_hf_hub=True) model = AutoModel.from_pretrained("blueskyfff/sd-controlnet-depth", from_hf_hub=True) - Notebooks
- Google Colab
- Kaggle
Download sd-controlnet-depth.pdparams from blueskyfff/sd-controlnet-depth: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/blueskyfff/sd-controlnet-depth/resolve/main/sd-controlnet-depth.pdparams
- Command line
-
hf download hf://blueskyfff/sd-controlnet-depth/sd-controlnet-depth.pdparams
-
curl -L -o sd-controlnet-depth.pdparams https://huggingface.co/blueskyfff/sd-controlnet-depth/resolve/main/sd-controlnet-depth.pdparams
1.45 GB
- Xet hash:
- 461f0d95811af3d13b5dbfce9a3b66cb3b462f612b911f6f16bf6b54a83964da
- Size of remote file:
- 1.45 GB
- SHA256:
- 6cb8a5c77d3363ddf9245a1725376f3b1db3ea244085d7ecf236aca5025cbc38
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