Here’s a pytorch example of a simple AI model:
import torch
import torch.nn as nn
# A tiny "model" = one linear layer
class TinyModel(nn.Module):
def __init__(self):
super().__init__()
self.fc = nn.Linear(3, 2) # input dim = 3, output dim = 2
def forward(self, x):
return self.fc(x)
model = TinyModel()
When you run this with pytorch:
torch.save(model.state_dict(), "tiny_model.pt")
It creates a file called tiny_model.pt which contains the trained parameters (weights + biases)