mbart large cc25

Introduction
MBART-LARGE-CC25 is a pretrained, multilingual model developed for translation tasks. It supports 25 languages, making it versatile for various text-to-text generation applications.

Architecture
The model is based on the MBART architecture, which is part of the broader transformers framework. It's designed to handle multiple languages efficiently and is implemented using PyTorch, with support for other libraries like TensorFlow.

Training
While the MBART-LARGE-CC25 model is pretrained, it is not finetuned. Users can finetune the model for specific tasks such as translation or summarization. The original training code is available through the PyTorch fairseq library, and a finetuning script is provided for further customization.

Guide: Running Locally
To run the model locally, follow these basic steps:

1. Install Dependencies: Ensure you have Python and the latest versions of PyTorch and the Transformers library installed.
2. Clone the Repository: Access the original code from the GitHub repository.
3. Download the Model: Use the Transformers library to download MBART-LARGE-CC25.
4. Run Inference: Utilize the model for translation tasks using the library's API.

For optimal performance, consider using cloud-based GPUs from providers such as AWS, GCP, or Azure.

License
The MBART-LARGE-CC25 model is available under the license terms specified in the original repository. Users should review these terms to ensure compliance with usage guidelines.