gpt2 spanish

Introduction

GPT2-Spanish is a language generation model specifically trained on Spanish texts. It uses a Byte Pair Encoding (BPE) tokenizer, tailored for the Spanish language, and inherits parameters from the small version of OpenAI's GPT-2 model. The model is adept at generating text based on learned patterns, although it may produce offensive or discriminatory content due to unfiltered training data.

Architecture

GPT2-Spanish employs a Byte Pair Encoding tokenizer with a byte-level approach for Unicode characters and a vocabulary size of 50,257. The model processes input sequences of 1,024 consecutive tokens, incorporating special tokens like "<|endoftext|>" and custom prompts "<|talk|>", "<|ax1|>", through "<|ax9|>".

Training

The model was trained using Hugging Face libraries on an Nvidia Tesla V100 GPU with 16GB of memory, hosted on Google Colab servers. The training corpus consisted of 11.5GB of Spanish texts, including 3.5GB from Wikipedia and 8GB from various books and literary works.

Guide: Running Locally

To run GPT2-Spanish locally:

1. Install Dependencies: Ensure you have Python and the Hugging Face Transformers library installed.
2. Download the Model: Access the model via Hugging Face's model hub.
3. Load the Model: Use the Transformers library to load the model and tokenizer.
4. Generate Text: Input a Spanish prompt to generate text using the model.

For optimal performance, consider using cloud-based GPUs like those offered by Google Colab, Amazon EC2, or Azure.

License

GPT2-Spanish is released under the MIT License, allowing for both personal and commercial use, with the requirement to include the original license and copyright notices in all copies or substantial portions of the software.