Instructions to use ThatOrJohn/efficientnet-b1-pineapple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThatOrJohn/efficientnet-b1-pineapple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ThatOrJohn/efficientnet-b1-pineapple") 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("ThatOrJohn/efficientnet-b1-pineapple") model = AutoModelForImageClassification.from_pretrained("ThatOrJohn/efficientnet-b1-pineapple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83b9a7aa8aafcfe103cb5eb9ff9681e7dc66d0dfeee7cb34c649eaffc5cb59ea
- Size of remote file:
- 5.11 kB
- SHA256:
- 427f9f4c5d7967050e88ec545d61914b76158ccde7b04f5b33cc54cacd96da6b
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