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:
- c063c6561b7ab908f0d7e9c4dc270617f8bc0111a714db65fec7f481a6c5ecd7
- Size of remote file:
- 627 Bytes
- SHA256:
- 1d2f8d5644864d856523bae0ede098144307fe585e171a2a4c5d5d7e03dda137
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.