Instructions to use jhoppanne/Dogs-Breed-Image-Classification-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhoppanne/Dogs-Breed-Image-Classification-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jhoppanne/Dogs-Breed-Image-Classification-V2") 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("jhoppanne/Dogs-Breed-Image-Classification-V2") model = AutoModelForImageClassification.from_pretrained("jhoppanne/Dogs-Breed-Image-Classification-V2") - Notebooks
- Google Colab
- Kaggle
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## Model description
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[Link to the fine-tuned model using resnet-50](https://huggingface.co/jhoppanne/Dogs-Breed-Image-Classification-V0)
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[Link to the fine-tuned model using resnet-101](https://huggingface.co/jhoppanne/Dogs-Breed-Image-Classification-V1)
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This model was trained using dataset from [Kaggle - Standford dogs dataset](https://www.kaggle.com/datasets/jessicali9530/stanford-dogs-dataset.)
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Quotes from the website:
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## Model description
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- [Link to the fine-tuned model using resnet-50](https://huggingface.co/jhoppanne/Dogs-Breed-Image-Classification-V0)
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- [Link to the fine-tuned model using resnet-101](https://huggingface.co/jhoppanne/Dogs-Breed-Image-Classification-V1)
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This model was trained using dataset from [Kaggle - Standford dogs dataset](https://www.kaggle.com/datasets/jessicali9530/stanford-dogs-dataset.)
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Quotes from the website:
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