Instructions to use models123/LongCat-Image-Dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use models123/LongCat-Image-Dev with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("models123/LongCat-Image-Dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vae/diffusion_pytorch_model.safetensors from models123/LongCat-Image-Dev: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/models123/LongCat-Image-Dev/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://models123/LongCat-Image-Dev/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/models123/LongCat-Image-Dev/resolve/main/vae/diffusion_pytorch_model.safetensors
168 MB
- Xet hash:
- 5fc08a93307850a89126de1e284972e1a1d7bcbb061ed06edcfc2db5a2669dcd
- Size of remote file:
- 168 MB
- SHA256:
- f5b59a26851551b67ae1fe58d32e76486e1e812def4696a4bea97f16604d40a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.