GPT OSS Release - Inference and Fine-Tuning

Learn to work with OpenAI's newly released open-source GPT models through comprehensive hands-on implementation covering inference, fine-tuning, and advanced optimization techniques. Explore the technical specifications and performance characteristics of the GPT OSS 20B parameter model, including its mixture of experts architecture and quantization capabilities using the innovative MXFP8 data type. Master running inference on these models using HuggingFace transformers, then dive deep into fine-tuning workflows with practical code examples and debugging strategies. Discover advanced fine-tuning techniques including TensorBoard integration for training visualization, validation split creation for model evaluation, and chat template inspection for proper data formatting. Gain insights into training parameter optimization, model preparation best practices, and development workflow management including SSH connections and version control integration. Access bonus content exploring the relationship between open-source and proprietary model architectures, providing strategic context for model selection and deployment decisions in production environments.