Instructions to use sngsfydy/MyResNet_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sngsfydy/MyResNet_50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sngsfydy/MyResNet_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("sngsfydy/MyResNet_50") model = AutoModelForImageClassification.from_pretrained("sngsfydy/MyResNet_50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a0d114acca0e2a4f8fb88342360ed4e366a6c56b1a01b8ab45a94fa379a150b
- Size of remote file:
- 94.4 MB
- SHA256:
- 63eb5f9fd49eceb1daa648b4cc178a62bab58c4eb4caf67b9ceeedcc7a91c27b
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