Instructions to use Nekshay/Car_VS_Rest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nekshay/Car_VS_Rest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nekshay/Car_VS_Rest") 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("Nekshay/Car_VS_Rest") model = AutoModelForImageClassification.from_pretrained("Nekshay/Car_VS_Rest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Custom_Object_Detection.ipynb from Nekshay/Car_VS_Rest: direct link, hf CLI and curl.
- Browser
- Download file 2.36 MB
-
https://huggingface.co/Nekshay/Car_VS_Rest/resolve/refs%2Fpr%2F4/Custom_Object_Detection.ipynb
- Command line
-
hf download hf://Nekshay/Car_VS_Rest@refs/pr/4/Custom_Object_Detection.ipynb
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curl -L -o Custom_Object_Detection.ipynb https://huggingface.co/Nekshay/Car_VS_Rest/resolve/refs%2Fpr%2F4/Custom_Object_Detection.ipynb
2.36 MB