The gpt-oss models provide full chain-of-thought, giving developers complete access to the model's reasoning process. This facilitates easier debugging and greater trust in outputs. The models are also fine-tunable, allowing developers to customize them to their specific use case through parameter fine-tuning. Additionally, the models have agentic capabilities, enabling the use of native capabilities for function calling, web browsing, Python code execution, and Structured Outputs.
The gpt-oss models are designed to be versatile and can be used with various inference partners and tools. The models can be used with Transformers, vLLM, PyTorch, Triton, and Metal, among others. The repository also includes reference implementations, tools, and client examples to help developers get started. The models are also compatible with various frameworks and libraries, making it easy to integrate them into existing workflows and applications.
