Instructions to use BioMike/classical_portrait_vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMike/classical_portrait_vae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="BioMike/classical_portrait_vae")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BioMike/classical_portrait_vae", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_conv_vae_256_epoch_304.pth from BioMike/classical_portrait_vae: direct link, hf CLI and curl.
- Browser
- Download file 118 MB
-
https://huggingface.co/BioMike/classical_portrait_vae/resolve/main/model_conv_vae_256_epoch_304.pth
- Command line
-
hf download hf://BioMike/classical_portrait_vae/model_conv_vae_256_epoch_304.pth
-
curl -L -o model_conv_vae_256_epoch_304.pth https://huggingface.co/BioMike/classical_portrait_vae/resolve/main/model_conv_vae_256_epoch_304.pth
118 MB
- Xet hash:
- 5c97c69036d60352932e2a15976bccb076cb71922c3b0390800bd5425fdde346
- Size of remote file:
- 118 MB
- SHA256:
- 5129aafa2ed48e0c234fe42353d69596867e1e74304292e752144bc3658654cf
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