Transformers outside python openvino transformer apis - ai

 How a transformer can live outside Python

Compiled inference runtimes – a pretrained model can be exported to a platform‑independent format (ONNX, TensorRT, OpenVINO, Core ML, etc.). Those files are then loaded by a lightweight C/C++ runtime that does the matrix math, so the only “installation” is the runtime library.
Native code implementations – you can write the transformer architecture yourself in C++, Rust, Java, Go, etc., and link it with a BLAS/LBLAS library (Intel MKL, OpenBLAS, etc.). The model weights are just numbers that you read from a file.
Hardware‑specific pipelines – some chips (GPUs, TPUs, neuromorphic boards) have their own SDKs that accept a transformer graph and run it without any Python stack.
No‑code platforms – services like Hugging Face Inference API, AWS SageMaker, Google Vertex AI, or Azure OpenAI let you call a transformer via a REST endpoint; you never install anything locally.