VeraSolutions PHI-3.5-MINI-FINETUNED-AMP-DATA-MODEL-500-STEPS-R-32-ALPHA-32

Introduction

The PHI-3.5-MINI-FINETUNED-AMP-DATA-MODEL-500-STEPS-R-32-ALPHA-32 is a text generation model developed by VeraSolutions. It is designed for efficient text generation tasks, leveraging advanced finetuning techniques on an existing model.

Architecture

This model is based on the unsloth/phi-3.5-mini-instruct-bnb-4bit model. It incorporates elements from multiple libraries and frameworks, including:

• Transformers for handling model architecture.
• Unsloth for faster training and deployment.
• TRL from Hugging Face for reinforcement learning integration. The model uses the Llama architecture, optimized for text-generation inference tasks.

Training

The model was finetuned using 500 training steps with parameters R-32 and Alpha-32. It was trained using Unsloth for doubling the training speed. The model is specifically designed to enhance text generation capabilities by finetuning it on specific data sets.

Guide: Running Locally

Basic Steps

1. Clone the Repository: Download the model files from the VeraSolutions repository on Hugging Face.
2. Install Dependencies: Ensure you have the necessary libraries such as Transformers, PyTorch, and any other specified dependencies.
3. Load the Model: Use the Transformers library to load the model into your environment.
4. Run Inference: Implement a script to input text data and generate predictions using the model.

Cloud GPUs

To optimize performance and speed, it is recommended to use cloud-based GPUs. Consider using platforms like AWS, Google Cloud, or Azure, which provide robust GPU support for machine learning tasks.

License

The PHI-3.5-MINI-FINETUNED-AMP-DATA-MODEL-500-STEPS-R-32-ALPHA-32 is distributed under the Apache 2.0 License, allowing for free use, modification, and distribution of the software.