Instructions to use dan-lara/Garbage-Classifier-Resnet-50-Finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dan-lara/Garbage-Classifier-Resnet-50-Finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dan-lara/Garbage-Classifier-Resnet-50-Finetuning") 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("dan-lara/Garbage-Classifier-Resnet-50-Finetuning") model = AutoModelForImageClassification.from_pretrained("dan-lara/Garbage-Classifier-Resnet-50-Finetuning") - Notebooks
- Google Colab
- Kaggle
Add model
Browse files- pytorch_model.pth +3 -0
pytorch_model.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:98a8d12babc17352cee551163e173d884f667863d9a682deb916d57f86be2703
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size 94439494
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