Command lines ============= mbext is used through its command line, ``python -m modelbuilder.builder``. This page documents the available options. Converting a model ------------------- .. code-block:: bash python -m modelbuilder.builder \ -m Qwen/Qwen3-8B \ -o qwen3-8b-cpu-int4 \ -p int4 \ -e cpu \ -c cache_dir Main arguments -------------- ``-m``, ``--model_name`` Model name on the Hugging Face hub. Do not use together with ``-i/--input``. ``-i``, ``--input`` Path to a local folder containing the Hugging Face ``config``, model and tokenizer, or the path to a float16/float32 GGUF file. ``-o``, ``--output`` Folder where the ONNX model and the additional files are written. ``-p``, ``--precision`` Precision of the model. One of ``int2``, ``int4``, ``int8``, ``int16``, ``bf16``, ``fp16`` or ``fp32``. ``-e``, ``--execution_provider`` Execution provider to target: ``cpu``, ``cuda``, ``dml``, ``webgpu`` or ``NvTensorRtRtx``. ``-c``, ``--cache_dir`` Cache directory for Hugging Face files and temporary ONNX external data files. Defaults to ``./cache_dir``. ``--private`` Convert a custom model implemented in separate files. See :doc:`private_model`. ``--extra_options`` Space-separated ``KEY=VALUE`` pairs controlling advanced behaviour (quantization block size, accuracy level, weight sharing, LoRA adapter, number of layers, and many more). Valid precision / execution provider combinations are: FP32 CPU, FP32 CUDA, FP16 CUDA, FP16 DML, BF16 CUDA, FP16 TRT-RTX, BF16 TRT-RTX, INT4 CPU, INT4 CUDA, INT4 DML and INT4 WebGPU. Full help --------- The authoritative and always up-to-date reference is the command's own help, which lists every ``--extra_options`` key with its description: .. code-block:: bash python -m modelbuilder.builder --help Running the private fast tests ------------------------------ When neither ``-m/--model_name`` nor ``-i/--input`` is provided, the ``fast-test-file`` from the ``--private`` option is executed as a script instead of converting a model: .. code-block:: bash python -m modelbuilder.builder --private "modeling.py;convert.py;test.py" In this mode ``-o``, ``-p`` and ``-e`` are not required. See :doc:`private_model`.