Writing an LLM from scratch, part 31 – the models are now on Hugging Face (www.gilesthomas.com)

In the latest installment of his series on creating a Large Language Model (LLM) from scratch, Sebastian Raschka has successfully trained seven models based on the GPT-2 architecture, which are now available on Hugging Face. These models include three trained locally on consumer-grade hardware and four fine-tuned in a cloud environment utilizing powerful GPUs. Raschka aims to optimize these models to match the performance of OpenAI's original weights while providing the community with resources for exploring and building upon his work. All models are shared under the Apache v2 open-source license, ensuring broad accessibility and legal clarity. This release is significant for the AI/ML community as it contributes to the growing pool of resources available for researchers and developers, particularly those looking to experiment with LLMs without the need for extensive computational resources. The models showcase different configurations and usage scenarios, allowing users to explore fine-tuning and deployment within the Hugging Face ecosystem. The author also emphasizes making the models user-friendly, allowing deeper integration with the Hugging Face Transformers library. This accessibility can foster collaboration and innovation within the community, pushing the boundaries of what can be achieved with large language models.