Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
Chinese
English
vit
huggingpics
Eval Results (legacy)
Instructions to use Bazaar/cv_construction_vehicle_identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bazaar/cv_construction_vehicle_identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Bazaar/cv_construction_vehicle_identification") 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("Bazaar/cv_construction_vehicle_identification") model = AutoModelForImageClassification.from_pretrained("Bazaar/cv_construction_vehicle_identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (715196548fde94bcf16a1ef857a05cdd7534b8c0) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>456f2c3
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