Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use malifiahm/vehicle_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malifiahm/vehicle_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="malifiahm/vehicle_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 AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("malifiahm/vehicle_classification") model = AutoModelForImageClassification.from_pretrained("malifiahm/vehicle_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from malifiahm/vehicle_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/malifiahm/vehicle_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://malifiahm/vehicle_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/malifiahm/vehicle_classification/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- bc7b8626bcf61168d2e694c12f448a0823cfa3c747cf030c6b50038b1d11b9a5
- Size of remote file:
- 4.73 kB
- SHA256:
- 1a03386ff6051a7bf1c331c3333c787c0d86606e3945f2108c1373632230f386
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