Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use nickmuchi/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickmuchi/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nickmuchi/vit-base-beans") 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("nickmuchi/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("nickmuchi/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 203 Bytes
9d88662 | 1 2 3 4 5 6 7 8 | {
"epoch": 8.0,
"eval_accuracy": 0.9849624060150376,
"eval_loss": 0.05050145834684372,
"eval_runtime": 1.4955,
"eval_samples_per_second": 88.935,
"eval_steps_per_second": 11.368
} |