Instructions to use hagerty7/recyclable-materials-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hagerty7/recyclable-materials-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hagerty7/recyclable-materials-classification") 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("hagerty7/recyclable-materials-classification") model = AutoModelForImageClassification.from_pretrained("hagerty7/recyclable-materials-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from hagerty7/recyclable-materials-classification: direct link, hf CLI and curl.
- Browser
- Download file 42 Bytes
-
https://huggingface.co/hagerty7/recyclable-materials-classification/resolve/main/README.md
- Command line
-
hf download hf://hagerty7/recyclable-materials-classification/README.md
-
curl -L -o README.md https://huggingface.co/hagerty7/recyclable-materials-classification/resolve/main/README.md
42 Bytes
ViT for Recyclable Material Classification