Instructions to use ags0504/diamond-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ags0504/diamond-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ags0504/diamond-classifier") 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("ags0504/diamond-classifier") model = AutoModelForImageClassification.from_pretrained("ags0504/diamond-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ags0504/diamond-classifier: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/ags0504/diamond-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ags0504/diamond-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ags0504/diamond-classifier/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- f67d6309d10f9325da8affe2c7f2c3fe11729b537599b8f9dfbb8f1630438bff
- Size of remote file:
- 343 MB
- SHA256:
- 08718b4ab6e4d2d99b3aab9a961fc4c08e1f19d5dadac5a1b184acad3fbb9eb7
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