MyOwnLLM is a custom implementation of a language model based on modern techniques in natural language processing (NLP) and deep learning. This project reflects my ability to develop and manage innovative solutions using cutting-edge technologies in the field of language models.
The development of MyOwnLLM has been inspired by the knowledge and examples provided in the book Natural Language Processing with Transformers by Lewis Tunstall, Leandro von Werra, and Thomas Wolf. This book has been a fundamental reference for understanding and applying the power of transformers and Hugging Face tools to real-world problems.
Throughout this project, I have adapted and extended the concepts and techniques presented in the book to create a model tailored to the specific needs of my application.
- Transformer-Based: MyOwnLLM leverages the transformer architecture to achieve efficient performance in tasks such as text generation, classification, and question answering.
- Advanced Customization: Implements unique adjustments and optimizations to address specific use cases.
- GPU Execution: Designed to run on platforms with GPU support, maximizing efficiency in both training and inference.