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 ·
6ff09de
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Parent(s): d3ed24d
Add pytorch_model_1941.pth and related files
Browse files- pytorch_model_1941.pth +3 -0
- training_metrics_1941.json +0 -0
pytorch_model_1941.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:48c4ec839213d94c1878c0589435a7b6e89ac882bde837b670adcf956b713c76
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training_metrics_1941.json
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