Instructions to use Suru/FruitModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Suru/FruitModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Suru/FruitModel") 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("Suru/FruitModel") model = AutoModelForImageClassification.from_pretrained("Suru/FruitModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 4.0, | |
| "total_flos": 3.657621909808742e+16, | |
| "train_loss": 0.13729210989549756, | |
| "train_runtime": 38.8164, | |
| "train_samples_per_second": 12.16, | |
| "train_steps_per_second": 0.824 | |
| } |