Fine-tune MNIST classifier (workshop demo) at 2026-01-13 15:49 UTC

README.md

@@ -1,41 +1,10 @@
 ---
-license: mit
-language: en
 tags:
-  - tutorial
-  - mnist
-  - pytorch
-task_categories:
-  - image-classification
-framework: pytorch
+- model_hub_mixin
+- pytorch_model_hub_mixin
 ---
 
-# MNIST Classifier (PyTorch)
-
-## What this model does
-This repository contains a simple feed-forward neural network trained to classify MNIST handwritten digits (0–9).
-
-## Intended use
-- Educational example for saving, uploading, and reloading a PyTorch model using the Hugging Face Hub.
-- Simple baseline digit classification for MNIST-like inputs.
-
-## How to use (inference)
-```python
-import torch
-
-loaded = ClassifierHF.from_pretrained("xiaziyna/test_classifier-hf")
-loaded.eval()
-
-with torch.no_grad():
-    logits = loaded(x)
-    preds = torch.argmax(logits, dim=1)
-```
-## Training data
-MNIST handwritten digits loaded via torchvision in the tutorial notebook.
-
-## Evaluation
-Test accuracy is printed in the notebook after training and after reloading from the Hub.
-
-## Limitations
-- This model is intended for teaching purposes only.
-- Performance depends on using the same preprocessing as training.
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Code: [More Information Needed]
+- Paper: [More Information Needed]
+- Docs: [More Information Needed]

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