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:
- 6caa9f93f74c3e3cc4a095462757a90bffa07dbb461b01b86b1a67860c795448
- Size of remote file:
- 687 MB
- SHA256:
- be595dd0b24f7c4a1865da6f6c0a37392254aed3ee33392c6b129d92ad047861
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.