Instructions to use jiew/mnist-torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiew/mnist-torch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jiew/mnist-torch") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("jiew/mnist-torch") model = AutoModelForImageClassification.from_pretrained("jiew/mnist-torch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jiew/mnist-torch: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/jiew/mnist-torch/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jiew/mnist-torch/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jiew/mnist-torch/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- d4e6400696f46baf1ba7a2edea3931b7ba256a1cc54aebdd7ed26744ccfe9d8a
- Size of remote file:
- 343 MB
- SHA256:
- 354112314c2a6a219b585b09197af8a67b09d110ba53b09d8cfdf8a93a2bbf1c
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