chandu1617/MNIST_with_MLP

MNIST MLP (fold-4 best)

Model: ImprovedMLP (2048 → 1024 → 512 → 256 → 128 → 10)
File: mlp_best_fold4.pth
Dataset: MNIST (mean 0.1307, std 0.3081)

Usage

from huggingface_hub import hf_hub_download
import torch, torch.nn as nn

class ImprovedMLP(nn.Module):
    def __init__(self):
        super().__init__()
        self.net = nn.Sequential(
            nn.Flatten(),
            nn.Linear(784,2048), nn.LayerNorm(2048), nn.GELU(), nn.Dropout(0.1),
            nn.Linear(2048,1024), nn.LayerNorm(1024), nn.GELU(), nn.Dropout(0.1),
            nn.Linear(1024,512), nn.LayerNorm(512), nn.GELU(), nn.Dropout(0.1),
            nn.Linear(512,256), nn.LayerNorm(256), nn.GELU(),
            nn.Linear(256,128), nn.LayerNorm(128), nn.GELU(),
            nn.Linear(128,10)
        )
    def forward(self,x): return self.net(x)

path = hf_hub_download("chandu1617/MNIST_with_MLP", "mlp_best_fold4.pth")
model = ImprovedMLP()
model.load_state_dict(torch.load(path))
model.eval()