xlm roberta large en ru

Introduction

The XLM-RoBERTa-Large-EN-RU model is a variant of XLM-RoBERTa designed to work with the most common tokens in English and Russian. It is optimized for tasks like feature extraction and text embeddings inference.

Architecture

The model is based on the XLM-RoBERTa architecture, which is a multilingual version of RoBERTa. It supports both English and Russian languages, and its embeddings and vocabulary have been reduced to include only the most frequent tokens in these languages.

Training

The model was trained using the standard procedures for XLM-RoBERTa, with a focus on optimizing it for English and Russian language tasks. The model's training involved reducing the vocabulary to enhance its efficiency and accuracy in these specific languages.

Guide: Running Locally

To run XLM-RoBERTa-Large-EN-RU locally, follow these steps:

1. Clone the repository or download the model files from the Hugging Face model page.
2. Install dependencies such as PyTorch and Transformers using pip install torch transformers.
3. Load the model in your script with the Hugging Face Transformers library.
4. Run inference to extract features or perform text embeddings.

For more efficient training and inference, consider using cloud GPUs such as those provided by AWS, Google Cloud, or Azure.

License

The model is subject to the licensing terms provided on the Hugging Face model page. Ensure compliance with any specific usage restrictions or requirements.