Instructions to use ashercn97/isaface-v6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use ashercn97/isaface-v6 with timm:
import timm model = timm.create_model("hf_hub:ashercn97/isaface-v6", pretrained=True) - Transformers
How to use ashercn97/isaface-v6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ashercn97/isaface-v6") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ashercn97/isaface-v6", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87c0440597b986c9fe40c8d6281f847fb974686bdcffa128ae4ae1e3b3fe0d7d
- Size of remote file:
- 6.21 MB
- SHA256:
- 6a839bc860c71f7c48014e45ea0dc4cd668ef0efc16edbd793b67eb837a20a23
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