Instructions to use kensvin/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kensvin/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kensvin/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("kensvin/image_classification") model = AutoModelForImageClassification.from_pretrained("kensvin/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7463fd66b128693d6280934403f5be2cd73c158015b15a67f7e92fae33e36214
- Size of remote file:
- 4.09 kB
- SHA256:
- 0bdd6d8d515a7c031e3ce7c8df15084dfdb360f309945891ee05174285feeaa8
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