Instructions to use Jan358/Geometric-Shapes-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jan358/Geometric-Shapes-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jan358/Geometric-Shapes-Classification") 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("Jan358/Geometric-Shapes-Classification") model = AutoModelForImageClassification.from_pretrained("Jan358/Geometric-Shapes-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-750/optimizer.pt from Jan358/Geometric-Shapes-Classification: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/Jan358/Geometric-Shapes-Classification/resolve/main/checkpoint-750/optimizer.pt
- Command line
-
hf download hf://Jan358/Geometric-Shapes-Classification/checkpoint-750/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Jan358/Geometric-Shapes-Classification/resolve/main/checkpoint-750/optimizer.pt
687 MB
- Xet hash:
- f8d33279635587faf5b6676d52344b920d050ef8017bed4224d61a7d4bd05060
- Size of remote file:
- 687 MB
- SHA256:
- 4e7b8773667c165c9b7ea1d9ea7b20c1d7ff46c21735b0201c4284ee44a97853
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