Instructions to use steven123/Check_GoodBad_Teeth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use steven123/Check_GoodBad_Teeth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="steven123/Check_GoodBad_Teeth") 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("steven123/Check_GoodBad_Teeth") model = AutoModelForImageClassification.from_pretrained("steven123/Check_GoodBad_Teeth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from steven123/Check_GoodBad_Teeth: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/steven123/Check_GoodBad_Teeth/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://steven123/Check_GoodBad_Teeth/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/steven123/Check_GoodBad_Teeth/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 914722de9d9f7d0ff7ca42c0ed3114b801e4cabf8e50854ee1621c8c9cf303ff
- Size of remote file:
- 343 MB
- SHA256:
- 93f59f46e7fa730b0a6af16c64904ccf7f91c51f3f5077273cebe75437665efc
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