DaFucV2 AI - Dynamic AI Model

This repository hosts the model for DaFucV2 AI, a dynamic AI architecture built using the Fractal Universe Chocolate Wafer Model (FUCWM). The model is designed to integrate with the DaFucV2 app, offering interactive conversational capabilities and adaptive thinking loops.

Model Overview

• Model Architecture: Combines a Variational Autoencoder (VAE) with fractal-like expanding layers based on complexity, using a FractalNode structure for dynamic growth.
• Self-Thinking and Feedback: Incorporates an iterative feedback mechanism allowing the model to send its own thoughts back into itself for further refinement.
• Applications: Optimized for conversational agents, adaptive feedback systems, and deeper multi-layered reasoning.
• Attention Mechanism: The model dynamically adjusts attention across fractal layers to modulate responses based on the complexity of the input.

DaFucV2 App Integration

The DaFucV2 AI model is designed to work seamlessly with the DaFucV2 app, available on GitHub. You can use the app to interact with the model, send queries, and explore its capabilities in real time.

Demo Video

Watch a video demonstration of me talking to the DaFucV2 AI here on YouTube.

Usage

To load and use the model within the app:

1. Download the app from the DaFucV2 GitHub repository.
2. Place the model (model.pth) in the appropriate directory.
3. Run the app by following the instructions in the repository.

To manually load the model in PyTorch:

import torch
from model import DynamicAI

# Load the saved model
model = DynamicAI(vocab_size=50000, embed_dim=256, latent_dim=256, output_dim=256, max_depth=7)
model.load_state_dict(torch.load("model.pth"))

# Set model to evaluation mode
model.eval()

# Example usage with input text
input_text = "Hello, how are you?"
response = model.chat(input_text)
print(response)