Instructions to use adhisetiawan/vit-base-patch16-224-finetuned-food102 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adhisetiawan/vit-base-patch16-224-finetuned-food102 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="adhisetiawan/vit-base-patch16-224-finetuned-food102") 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("adhisetiawan/vit-base-patch16-224-finetuned-food102") model = AutoModelForImageClassification.from_pretrained("adhisetiawan/vit-base-patch16-224-finetuned-food102", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.998954339491112, | |
| "total_flos": 2.1353596059581743e+19, | |
| "train_loss": 4.144423897296315, | |
| "train_runtime": 8280.2172, | |
| "train_samples_per_second": 33.26, | |
| "train_steps_per_second": 0.26 | |
| } |