Instructions to use BlakeMartin/BeanDetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BlakeMartin/BeanDetect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="BlakeMartin/BeanDetect") 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("BlakeMartin/BeanDetect") model = AutoModelForImageClassification.from_pretrained("BlakeMartin/BeanDetect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e491936b96120c40e17d4f66c9d77b5144c84ab9382b1d36187334982abeb0f3
- Size of remote file:
- 687 MB
- SHA256:
- 3ef093cf0c329c5d6f2acd29e1e88a912a65cce3a680490ccb733594e2f5fc36
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