Instructions to use dima806/smoker_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/smoker_image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/smoker_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("dima806/smoker_image_classification") model = AutoModelForImageClassification.from_pretrained("dima806/smoker_image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a31b3719f4dcf2d78a80dd32cd02a2f1d6533d913d5b4bddae35f4e20886506c
- Size of remote file:
- 4.41 kB
- SHA256:
- 86f0cc416eb948b77e4a758e5142b81c862b9457335a156b939e3a62f8ea29a6
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