Instructions to use StemsOut/test-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StemsOut/test-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="StemsOut/test-beans") 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("StemsOut/test-beans") model = AutoModelForImageClassification.from_pretrained("StemsOut/test-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e35136f5f68e570168b80e216f437262521db77b8bfec21789bd1a069cc01131
- Size of remote file:
- 687 MB
- SHA256:
- 051a4a5cd63aeb00cc8c4873395e9155d0aa6f86ce00d81a57c5b742606b4a25
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.