Instructions to use gary2002/output_dir-full_dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gary2002/output_dir-full_dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gary2002/output_dir-full_dataset") 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("gary2002/output_dir-full_dataset") model = AutoModelForImageClassification.from_pretrained("gary2002/output_dir-full_dataset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09b2f49a04dac94799f75d30598215e5532752473ac9b9b0ad7377483e644cd3
- Size of remote file:
- 5.05 kB
- SHA256:
- 8116f09c373d0d0afd346eb179d4dcf7b185cb632836ffdc1ef80def60a32a3c
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