Instructions to use CharlesCGCTG/model_resnet-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CharlesCGCTG/model_resnet-50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="CharlesCGCTG/model_resnet-50") 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("CharlesCGCTG/model_resnet-50") model = AutoModelForImageClassification.from_pretrained("CharlesCGCTG/model_resnet-50") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02a7624a8cea75328059bd7863d3e3866a3afa12ea7a1c249343b79dd0837318
- Size of remote file:
- 5.37 kB
- SHA256:
- b9a62b2786de24232bb1bc88230c76bbca3cd011affd695915dc8875897982e6
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