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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f08e49e20e737a6bc85f8514f642b1e9783e14afbab7a3dc81c868130faa3011
- Size of remote file:
- 348 MB
- SHA256:
- 92eaeff6fa3efb84d8dbf01ba1a3c133da24f9da998f1b33583bcfd5c410646b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.