Machine Translation

This repository contains machine translation models based on seq2seq architecture. There are two models included: English to Spanish translation and English to French translation. Both models are trained on a large corpus of text data and are available for public use.

English to Spanish Translation

The English to Spanish translation model is a relatively large model with ~23 million parameters. It achieves an accuracy of 95 percent on the test data. The model is based on a seq2seq architecture and uses an attention mechanism to focus on relevant parts of the input sentence.

To use the English to Spanish translation model, follow these steps:

1. Download the "English to Spanish" folder from the repository.
2. Download the pre-trained model stored in the releases section (right side of repo page).
3. Open the notebook and run the code.

English to French Translation

The English to French translation model is a relatively small model with ~1 million parameters that achieves an accuracy of 99 percent on its limited vocabulary. It is also based on a seq2seq architecture and uses an attention mechanism to focus on relevant parts of the input sentence.

To use the English to French translation model, follow these steps:

1. Download the "English to French" folder from the repository.
2. Open the notebook and run the code.

Running the Notebooks on Google Colaboratory

Both models can be run on Google Colaboratory, a free online platform for running Jupyter notebooks. To run the notebooks on Google Colaboratory, follow these steps:

1. Upload the notebooks and files to your Google Drive.
2. Open Google Colaboratory and create a new notebook.
3. Mount your Google Drive to the notebook using the following code:

from google.colab import drive
drive.mount('/content/drive')

4. Navigate to the folder where you uploaded the notebooks and files using the following code:

%cd /content/drive/MyDrive/your-folder-name

5. Run the code in the notebook.