Instructions to use ashercn97/isaface-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use ashercn97/isaface-v3 with timm:
import timm model = timm.create_model("hf_hub:ashercn97/isaface-v3", pretrained=True) - Transformers
How to use ashercn97/isaface-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ashercn97/isaface-v3") 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-v3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 170f4f7fc6c372f0dcdcb3b5d77531ae06371817ea2b2d90258b4faaa1e59c56
- Size of remote file:
- 350 MB
- SHA256:
- 4961e9fcc9318e01ffc28e465efdbfe7797d9f36e42dce9276e1ca2270f7bbf8
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