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Higher-Order-Functional (HOF) Cognitive Model Trainer

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HOF Cognitive Model Training on Hugging Face

This document demonstrates the training of a HOF cognitive model on Hugging Face, including HOF cognitive agent chaining with a fine-tuned model.

Installation

First, install the necessary dependencies:

pip install -r requirements.txt

Usage

Step 1: Fine-tuning a Small Model

Run the fine-tuning script:

python -m hof_cognitive_model_training.fine_tuning

Step 2: Upload to Hugging Face

Run the upload script:

python -m hof_cognitive_model_training.upload_model --token YOUR_HUGGINGFACE_TOKEN

Replace YOUR_HUGGINGFACE_TOKEN with your actual Hugging Face token.

Step 3: Implement HOF Cognitive Chaining

Run the cognitive chaining script:

python -m hof_cognitive_model_training.cognitive_chaining --username YOUR_USERNAME

Replace YOUR_USERNAME with your actual Hugging Face username.

Summary

  1. Fine-tune a small model: Using Hugging Face’s Trainer API.
  2. Upload the model: To Hugging Face’s Model Hub.
  3. Set up HOF Cognitive Agents: Using the fine-tuned model.
  4. Implement chaining: Based on the Functionally Atomic Development Paradigm and other provided documents.

For complete implementation details, refer to the specific requirements and configurations from the provided documents.

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