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
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### Dataset Waste Classification :
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```bibtex
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@misc
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{garbageDatasetResNet24,
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author = {Ferreira et al.},
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title = {8 classes Garbage Dataset for ResNet},
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year = {2024},
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### Dataset Waste Classification :
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```bibtex
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@misc{garbageDatasetResNet24,
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author = {Ferreira et al.},
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title = {8 classes Garbage Dataset for ResNet},
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year = {2024},
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