Instructions to use OttoYu/TreeDisease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OttoYu/TreeDisease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OttoYu/TreeDisease") 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("OttoYu/TreeDisease") model = AutoModelForImageClassification.from_pretrained("OttoYu/TreeDisease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- vision
- image-classification
datasets:
- OttoYu/TreeDisease
widget: null
Validation Metrics
- Loss: 1.558
- Accuracy: 0.564
- Macro F1: 0.488
- Micro F1: 0.564
- Weighted F1: 0.516
- Macro Precision: 0.503
- Micro Precision: 0.564
- Weighted Precision: 0.542
- Macro Recall: 0.545
- Micro Recall: 0.564
- Weighted Recall: 0.564