Instructions to use lamnt2008/bicycle_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lamnt2008/bicycle_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lamnt2008/bicycle_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("lamnt2008/bicycle_model") model = AutoModelForImageClassification.from_pretrained("lamnt2008/bicycle_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ef8d10a5de9a88a9f3b9fc3e4054ae6c9786e897895b6bdc8327b09115600ca
- Size of remote file:
- 687 MB
- SHA256:
- b35b770d8d9a1d972e1ca4150bc7db5473aa0d4a013a2b6da74180a3868e4824
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