JUPYTER NOTEBOOKS

Machine Translation & LLM Notebooks

A collection of Jupyter notebooks exploring machine translation, large language models, and evaluation metrics

Featured Notebook

Building a Neural Machine Translation System

Implementation of a Transformer-based machine translation system from scratch using PyTorch.

PyTorchTransformersNLTK
Open in ColabView Source
Building a Neural Machine Translation System
Large Language Models

Fine-tuning LLMs for Specialized Tasks

Explore techniques for fine-tuning large language models on domain-specific tasks using LoRA and QLoRA.

PyTorchTransformersPEFT
Open in Colab
Evaluation

Advanced MT Evaluation Metrics

Implementation and analysis of BLEU, METEOR, TER, and BERTScore for machine translation evaluation.

PythonSacreBLEUBERTScore
Open in Colab

Getting Started

Prerequisites

  • Basic understanding of Python and PyTorch
  • Familiarity with neural networks and transformers
  • Google Colab account for running notebooks
  • Basic knowledge of NLP concepts

Setup Instructions

  1. 1Clone the repository from GitHub
  2. 2Open notebooks in Colab or local Jupyter environment
  3. 3Install required dependencies using pip
  4. 4Follow along with the step-by-step instructions