Instructions to use ashercn97/isaface-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use ashercn97/isaface-v5 with timm:
import timm model = timm.create_model("hf-hub:ashercn97/isaface-v5", pretrained=True) - Transformers
How to use ashercn97/isaface-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ashercn97/isaface-v5") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ashercn97/isaface-v5") model = AutoModelForImageClassification.from_pretrained("ashercn97/isaface-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ashercn97/isaface-v5: direct link, hf CLI and curl.
- Browser
- Download file 6.21 MB
-
https://huggingface.co/ashercn97/isaface-v5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ashercn97/isaface-v5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ashercn97/isaface-v5/resolve/main/pytorch_model.bin
6.21 MB
- Xet hash:
- 3f42c814e921f61ab1c0c363a8b5562a778743faaac83f1e66a30e00a9511aa3
- Size of remote file:
- 6.21 MB
- SHA256:
- eec6bec17bba07e268a05d744e1a3f03d4e1b8084ec2563ae259e9a12921d3a0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.