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")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Nekshay/Car_VS_Rest") model = AutoModelForImageClassification.from_pretrained("Nekshay/Car_VS_Rest") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:43396bb6b4b3ca126c9044b7b09deab338cf6d876ab6f5421f0d727cf3cd1ec3
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size 347502916
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