Image Classification
Transformers
TensorBoard
Safetensors
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use punchnami/ViT-Base-Pothole-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use punchnami/ViT-Base-Pothole-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="punchnami/ViT-Base-Pothole-Classification") 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("punchnami/ViT-Base-Pothole-Classification") model = AutoModelForImageClassification.from_pretrained("punchnami/ViT-Base-Pothole-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 203 Bytes
60b5fcc | 1 2 3 4 5 6 7 8 | {
"epoch": 3.0,
"eval_accuracy": 0.9668874172185431,
"eval_loss": 0.11718238145112991,
"eval_runtime": 161.4495,
"eval_samples_per_second": 3.741,
"eval_steps_per_second": 0.471
} |