Instructions to use steven123/Teeth_C with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use steven123/Teeth_C with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="steven123/Teeth_C") 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/Teeth_C") model = AutoModelForImageClassification.from_pretrained("steven123/Teeth_C", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from steven123/Teeth_C: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/steven123/Teeth_C/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://steven123/Teeth_C/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/steven123/Teeth_C/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 4a08472dfc5db443af39a5d6d08a58ed93261d07e485d391433cdf6657277043
- Size of remote file:
- 343 MB
- SHA256:
- 46a30e9592a2bfa2a9514acff6bcbdef5b135341dacb6d71b69df195c2d04778
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