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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25d50c31cab01358eacb4fb8c834c99bbcf8cb57135604fe031a95d819e213e9
- Size of remote file:
- 343 MB
- SHA256:
- 7c75b23eb498f016d7c9d83fbf1734054aff064a0a75164db839e9333e0f1302
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