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:
- 693c59848fbe72191faef47c161f82bb6d821472768b093e85b1efcf91f84e56
- Size of remote file:
- 343 MB
- SHA256:
- c48a261af8e2ac537ab7e46fc3d09cb0a6aea192582e1a57cd5a82de6ec597f4
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