Instructions to use DeepLearner101/ResNet50FTCIFAR100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ResNet50FTCIFAR100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ResNet50FTCIFAR100") 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("DeepLearner101/ResNet50FTCIFAR100") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ResNet50FTCIFAR100") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 869c54e
Add pytorch_model_2016.pth and related files
Browse files- pytorch_model_2016.pth +3 -0
- training_metrics_2016.json +0 -0
pytorch_model_2016.pth
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oid sha256:96eac38323d392818e987ece16bb9db9b8b181c8099ea78a8751de08b5a6cea0
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training_metrics_2016.json
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