sahiljani / AIDI_1002_Final_Project

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TinyLLM

This repository contains the code and instructions for fine-tuning the TinyLLM model on a color dataset and using it to describe colors based on their names.

Folder Structure

  • tinyLLM_model/: Contains TinyLLM model.
  • contribution/: TinyLLM with new datasets for evaluation in various contexts.

Installation

!pip install accelerate peft bitsandbytes transformers trl

Data Preparation

The color dataset used for fine-tuning is located at burkelibbey/colors. The data is reformatted to fit the ChatML format.

Fine-Tuning

  • Load the dataset and prepare the training data.
  • Initialize the TinyLLM model and tokenizer.
  • Configure LoRA (LoraConfig) and training arguments.
  • Train the model using SFTTrainer from trl.

Merging with Base Model

After fine-tuning, the LoRA is merged with the base TinyLLM model to produce the final model.

Inference

Generate color descriptions using the fine-tuned TinyLLM model.

Usage

  1. Fine-tune the TinyLLM model by running the provided notebook.
  2. dd the Hugging Face token to your notebook with the name HF_TOKEN as the Secret key.
  3. Generate color descriptions using the generate_response function.
generate_response(user_input='Yellow color')

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