opus mt et en

Introduction

The OPUS-MT-ET-EN model is developed by the Language Technology Research Group at the University of Helsinki. It is designed for translation from Estonian (et) to English (en) using the OPUS dataset. This model is part of the OPUS-MT project and utilizes transformer-based architecture for text-to-text generation tasks.

Architecture

The OPUS-MT-ET-EN model employs a transformer-align architecture with preprocessing steps that include normalization and SentencePiece tokenization. It is designed for efficient translation tasks between the Estonian and English languages.

Training

The model is trained on the OPUS dataset, which features extensive multilingual data. The preprocessing involves normalization and the use of SentencePiece for tokenization. The original weights and test sets can be downloaded via provided links, including opus-2019-12-18.zip for weights and corresponding test and evaluation data.

Guide: Running Locally

To run the OPUS-MT-ET-EN model locally, follow these steps:

1. Install Dependencies: Ensure you have PyTorch or TensorFlow installed, as the model is compatible with both frameworks.
2. Download the Model: Clone the model repository from Hugging Face or download the model weights directly.
3. Load the Model: Use the Hugging Face Transformers library to load the model and tokenizer.
4. Run Inference: Input your Estonian text to receive English translations.

For faster performance, consider using a cloud GPU service like AWS, GCP, or Azure.

License

The OPUS-MT-ET-EN model is released under the Apache 2.0 License, allowing for both personal and commercial use with minimal restrictions.