Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use griffio/vit-large-patch16-224-dungeon-geo-morphs-009 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use griffio/vit-large-patch16-224-dungeon-geo-morphs-009 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="griffio/vit-large-patch16-224-dungeon-geo-morphs-009") 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("griffio/vit-large-patch16-224-dungeon-geo-morphs-009") model = AutoModelForImageClassification.from_pretrained("griffio/vit-large-patch16-224-dungeon-geo-morphs-009") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 23.285714285714285, | |
| "eval_accuracy": 1.0, | |
| "eval_loss": 0.0428813174366951, | |
| "eval_runtime": 0.611, | |
| "eval_samples_per_second": 58.923, | |
| "eval_steps_per_second": 8.184 | |
| } |