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  # French to English Machine Translation
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  ## 1. Introduction
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  This project aims to develop a machine translation system for translating French text into English. The system utilizes state-of-the-art neural network architectures and techniques in natural language processing (NLP) to accurately translate French sentences into their corresponding English equivalents.
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  ## 2. Model Architecture
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  The machine translation model employs a sequence-to-sequence architecture, specifically utilizing a recurrent neural network (RNN) with an attention mechanism. The model is trained on a parallel corpus consisting of aligned French and English sentences. Key components of the model include encoder and decoder networks, attention mechanism, and tokenization for text processing.
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## 3. How-to Guide
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  ### 3.1. Data Preparation
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  - Gradio is utilized for deploying the trained model.
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  - Users can input a French text, and the model will translate it to English.
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  ## 4. License
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  This project is licensed under the [MIT License](LICENSE).
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  ## 5. Contributors
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- - Kamelia Zaman Moon
 
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  # French to English Machine Translation
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+ - **Author:** Kamelia Zaman Moon
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+ - **Project link:** https://huggingface.co/spaces/KameliaZaman/French-to-English-Translation
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+ - **Language(s):** Python
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+ - **License:** MIT
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+ - **Contact:** kamelia.stu2017@juniv.edu
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+
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+ ## Table of Contents
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+ - [Introduction](#introduction)
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+ - [Model Architecture](#model-architecture)
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+ - [How-to Guide](#how-to-guide)
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+ - [License](#license)
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+ - [Contributors](#contributors)
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+
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  ## 1. Introduction
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  This project aims to develop a machine translation system for translating French text into English. The system utilizes state-of-the-art neural network architectures and techniques in natural language processing (NLP) to accurately translate French sentences into their corresponding English equivalents.
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  ## 2. Model Architecture
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  The machine translation model employs a sequence-to-sequence architecture, specifically utilizing a recurrent neural network (RNN) with an attention mechanism. The model is trained on a parallel corpus consisting of aligned French and English sentences. Key components of the model include encoder and decoder networks, attention mechanism, and tokenization for text processing.
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+ ```
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+ ── eng_-french.csv - text dataset.
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+
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+ ── french_to_english_translator.h5 - generated model.
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+
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+ ── french_to_english_translation_using_seq2seq.ipynb - preprocesses input, trains, saves and evaluates the model.
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+
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+ ── app.py - this module starts the app interface.
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+
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+ ── README.md - readme file of this project.
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+
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+ ── requirements.txt - list of required packages.
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+ ```
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  ## 3. How-to Guide
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  ### 3.1. Data Preparation
 
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  - Gradio is utilized for deploying the trained model.
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  - Users can input a French text, and the model will translate it to English.
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+ ```bash
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+ # clone project
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+ git clone https://huggingface.co/spaces/KameliaZaman/French-to-English-Translation/tree/main
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+
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+ # go inside the project directory
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+ cd French-to-English-Translation
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+
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+ # install the required packages
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+ pip install -r requirements.txt
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+
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+ # run the gradio app
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+ python app.py
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+ ```
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+
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  ## 4. License
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  This project is licensed under the [MIT License](LICENSE).
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  ## 5. Contributors
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+ - Kamelia Zaman Moon - kamelia.stu2017@juniv.edu