text generation news gpt2 small hungarian

Introduction

The Hungarian GPT-2 News Generator is a text generation model developed for generating Hungarian language content. It is based on the GPT-2 architecture and specifically finetuned for Hungarian news articles.

Architecture

This model leverages the GPT-2 architecture, utilizing transformers for text generation tasks. It is built on the PyTorch framework, facilitating efficient implementation and experimentation. The model was pretrained on the Hungarian Wikipedia and further finetuned using a curated news corpus from Hungarian news outlets like hvg.hu, index.hu, and nol.hu.

Training

The model was initially pretrained on a broad dataset from Hungarian Wikipedia to capture a wide range of linguistic features. Subsequently, it was finetuned on a specific corpus of Hungarian news articles to enhance its ability to generate contextually relevant and stylistically appropriate news content. The perplexity scores achieved during testing were 47.46 for poems and 22.06 for news, indicating the model's proficiency in handling news text.

Guide: Running Locally

To run the Hungarian GPT-2 News Generator locally, follow these steps:

1. Clone the Repository: Access the model files via the Hugging Face repository or the GitHub repository.
2. Install Dependencies: Ensure you have Python and PyTorch installed. Additional dependencies can be installed using a package manager like pip.
3. Download Model: Obtain the model weights from the Hugging Face model hub.
4. Execute Inference Script: Use the provided scripts to generate text based on input prompts.

For optimal performance and faster text generation, it is recommended to use cloud GPUs such as those provided by AWS, Google Cloud, or Azure.

License

The Hungarian GPT-2 News Generator is available under the MIT License, allowing for flexible use and modification of the codebase.