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:
- 696c7beb9611c19848e7707a444c54d221286259fa2bf66dc55e7770366d9572
- Size of remote file:
- 343 MB
- SHA256:
- feba1c4c2c0f529b53729cb13aa3a93e558a489dab82e2f18708cd64e8374cb1
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