darcy132/mnist-mlp

MNIST MLP Classifier

A simple 2-layer MLP trained on MNIST.

Model Info

• Input: 28×28 grayscale image (flattened)
• Hidden size: 128, Dropout: 0.2
• Output: 10 classes (digits 0–9)

Usage

import torch
import torch.nn as nn

class MLP(nn.Module):
    def __init__(self, hidden_size=128, dropout=0.2):
        super().__init__()
        self.net = nn.Sequential(
            nn.Flatten(),
            nn.Linear(28*28, hidden_size), nn.ReLU(), nn.Dropout(dropout),
            nn.Linear(hidden_size, hidden_size), nn.ReLU(), nn.Dropout(dropout),
            nn.Linear(hidden_size, 10),
        )
    def forward(self, x):
        return self.net(x)

from huggingface_hub import hf_hub_download
path = hf_hub_download(repo_id="你的用户名/mnist-mlp", filename="model.pth")
model = MLP()
model.load_state_dict(torch.load(path, map_location="cpu"))
model.eval()