Image Classification
Transformers
Safetensors
English
siglip
tooth
SigLIP2
chemistry
biology
medical
Calculus
Mouth Ulcer
hypodontia
Tooth Discoloration
Gingivitis
tooth-agenesis
Instructions to use replyquickflorida/tooth-agenesis-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use replyquickflorida/tooth-agenesis-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="replyquickflorida/tooth-agenesis-model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("replyquickflorida/tooth-agenesis-model") model = AutoModelForImageClassification.from_pretrained("replyquickflorida/tooth-agenesis-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-385/optimizer.pt from replyquickflorida/tooth-agenesis-model: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/replyquickflorida/tooth-agenesis-model/resolve/main/checkpoint-385/optimizer.pt
- Command line
-
hf download hf://replyquickflorida/tooth-agenesis-model/checkpoint-385/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/replyquickflorida/tooth-agenesis-model/resolve/main/checkpoint-385/optimizer.pt
687 MB
- Xet hash:
- ed3c3e6fe1904aaff895c322b2212098ee680f2c94fe81e2ac57fc88a42b8e69
- Size of remote file:
- 687 MB
- SHA256:
- 1c24ea3ed574fc4e9c0b28cffd579c776c41c177f2df27d9495966cc12d1f1e8
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