Instructions to use fxmarty/resnet-tiny-mnist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/resnet-tiny-mnist with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fxmarty/resnet-tiny-mnist") 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("fxmarty/resnet-tiny-mnist") model = AutoModelForImageClassification.from_pretrained("fxmarty/resnet-tiny-mnist") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 551c717fe31df015b7c317aa0c6375a50ed526be52b83318a0d0f23adb2aec95
- Size of remote file:
- 3.06 kB
- SHA256:
- aa4e95a4ea032aa40c0216647955b0d7d2e98a98aba8f2db221e4606d6d0d474
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