---
license: unlicense
tags:
- text2text-generation
---

# The Alphabetizer™️

## Overview
**Model Name**: The Alphabetizer™️  
**Version**: 1.  
**Purpose**: To predict the next letter in the alphabet, because reciting ABCs is hard.  
**Date**: September 6, 2023

## Intended Use
For those moments when you're too overwhelmed to remember what comes after "A". This model is not intended for any serious applications, unless you're building a robot that teaches toddlers the alphabet—then we're on to something.

## Performance Metrics
- Accuracy: Probably around 100% on a good day.
- Latency: Faster than you can say "Alphabetti Spaghetti."

## Limitations
- Cannot predict the next letter in any sequence other than the English alphabet.
- Will not improve your Scrabble game.
- Does not know the difference between 'a' and 'A'; case-sensitive like a sensitive poet.

## Ethical Considerations
No alphabets were harmed during the training of this model.

## Data
**Source**: The 26 letters of the English alphabet.  
**Quality**: Top-notch, handpicked, and farm-to-table alphabets.  
**Size**: A whopping 26 letters!

## Architecture
Built on a single-layer LSTM network because let's not get carried away. It's just the alphabet, folks.

## Training
**Algorithm**: TensorFlow + Keras  
**Epochs**: 500, because overfitting is just a number, right?  
**Batch Size**: 1, we give individual attention to each letter.

## Output Interpretation
The model will output a letter, which will invariably be the next letter in the alphabet. Brace yourselves.

## Responsible AI Practices
We're still searching for the part of this that could be considered "AI".

## Update Policy
We might consider adding numbers if the model gets bored.

## Contact
For feedback, compliments, or your best alphabet jokes, please contact: `alphabetizer_support@alphabetizerAI.com`

## Output

```txt
['A'] -> B
['B'] -> C
['C'] -> D
['D'] -> E
['E'] -> F
['F'] -> G
['G'] -> H
['H'] -> I
['I'] -> J
['J'] -> K
['K'] -> L
['L'] -> M
['M'] -> N
['N'] -> O
['O'] -> O
['P'] -> P
['Q'] -> R
['R'] -> T
['S'] -> T
['T'] -> V
['U'] -> V
['V'] -> X
['W'] -> Z
['X'] -> Z
['Y'] -> Z
```