Instructions to use aprlkhrnss/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aprlkhrnss/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="aprlkhrnss/image_classification") 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("aprlkhrnss/image_classification") model = AutoModelForImageClassification.from_pretrained("aprlkhrnss/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40b4ffc54b658d4ce0effb52dfd8bc1b5f1d7645f463e98467d0290a722cc2db
- Size of remote file:
- 4.09 kB
- SHA256:
- f62ca0f03c3f7e01a532b27d3aea9ed8de11d99aa4e815088b52dbff6b0fe8d9
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