Instructions to use DamarJati/plastic-recycling-codes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DamarJati/plastic-recycling-codes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DamarJati/plastic-recycling-codes") 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("DamarJati/plastic-recycling-codes") model = AutoModelForImageClassification.from_pretrained("DamarJati/plastic-recycling-codes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c8156d7c34883f072a4fa3d5f55737a3f51b7aac7fdab621ae99e4cfaf27be2
- Size of remote file:
- 110 MB
- SHA256:
- d1a52f5a72eacff5fba534b3833edafa01ddb213ca7e60fe9b6c0c1516e72615
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.