spanish gpt2

Introduction

The Spanish GPT-2 model is a language model trained from scratch on a large corpus of Spanish text. This project was part of the Flax/JAX Community Week, organized by Hugging Face, with TPU resources sponsored by Google.

Architecture

This model is based on the GPT-2 architecture, which is designed for text generation tasks. It uses the Flax library for model implementation and JAX for efficient mathematical computations.

Training

The model was trained on the large_spanish_corpus, a dataset of approximately 20 GB. The training utilized 95% of the data, with the remaining 5% used for validation. The resulting evaluation metrics include a loss of 2.413 and a perplexity of 11.36.

Guide: Running Locally

To run the Spanish GPT-2 model locally, follow these steps:

1. Clone the Model Repository: Start by cloning the model's repository from Hugging Face.
2. Set Up Environment: Install the necessary libraries such as Transformers, PyTorch, and JAX.
3. Load the Model: Use the Transformers library to load the Spanish GPT-2 model.
4. Generate Text: Input a text prompt to generate Spanish text using the model.

For optimal performance, consider using a cloud-based GPU service such as Google Colab or AWS EC2 with GPU support.

License

The Spanish GPT-2 model is licensed under the MIT License, which permits reuse, modification, and distribution with attribution.