Instructions to use zoumana/beans_health_type_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zoumana/beans_health_type_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="zoumana/beans_health_type_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("zoumana/beans_health_type_classifier") model = AutoModelForImageClassification.from_pretrained("zoumana/beans_health_type_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from zoumana/beans_health_type_classifier: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/zoumana/beans_health_type_classifier/resolve/main/optimizer.pt
- Command line
-
hf download hf://zoumana/beans_health_type_classifier/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/zoumana/beans_health_type_classifier/resolve/main/optimizer.pt
687 MB
- Xet hash:
- 16a4a0cbefb27c0280126942b8a0d5d101f72bda9981450a82f85728e2c7211f
- Size of remote file:
- 687 MB
- SHA256:
- cf0cbd59d2e69759160d5a94d8197ca1216768a9a967b676c1fc979cb83760e3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.