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:
- 03aa007515e61927caf5a3578de6b2af96636807c8ca5aa76bad8cea52c91548
- Size of remote file:
- 343 MB
- SHA256:
- a8c6b72a5d39008af8bf9713f35b873f546965b624c02079cd9a58d414e04ae5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.