| | --- |
| | license: mit |
| | language: |
| | - en |
| | tags: |
| | - arithmetic |
| | - regression |
| | - mathematics |
| | --- |
| | # Axiom Model |
| |
|
| | ## Description |
| | The Axiom Model is a beta version designed to perform basic arithmetic operations. It leverages a neural network to predict the result of arithmetic expressions based on synthetic data. |
| |
|
| | ## Model Details |
| | - **Type**: Neural Network for Arithmetic Operations |
| | - **Version**: Beta |
| | - **Creator**: Maw Studio (aka Maw Lab) |
| | - **File**: [axiom_model.pth](./axiom_model.pth) |
| |
|
| | ## Usage |
| | This model can be used to evaluate basic arithmetic operations. It has been trained on a large dataset to provide accurate results for addition, subtraction, multiplication, and division. |
| |
|
| | ### Example |
| | ```python |
| | import torch |
| | |
| | # Load the model |
| | model = torch.load('path_to_model/axiom_model.pth') |
| | model.eval() |
| | |
| | # Example input |
| | input_tensor = torch.tensor([[1.0, 2.0, 0]]) # Example: 1 + 2 |
| | output = model(input_tensor) |
| | |
| | print(f'Result: {output.item()}') |
