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Mlc_llm_convert_weights

As explained in Domain-Specific Small Language Models

An MLC LLM command that converts model weights into MLC format using specified quantization settings.

mlc_llm_convert_weights converts cloned model weights into MLC LLM format for a specified quantization type, target device, and output directory. It prepares weights for later configuration, compilation, and inference rather than serving the model by itself. section 11.3 section 11.5

A practical conversion workflow includes:

  • Clone the model weights and configuration files, using Git LFS when required. section 11.3
  • Choose quantization and a device, then write converted weights to a destination directory. section 11.3
  • Generate chat configuration separately with mlc_llm_gen_config before compiling a platform-specific model library. section 11.3 section 11.5

CUDA conversion with q4f16_1

mlc_llm convert_weight ./RedPajama-INCITE-Instruct-3B-v1/ --quantization q4f16_1 --device cuda -o dist/RedPajama-INCITE-Instruct-3B-v1-q4f16_1-MLC

How Domain-Specific Small Language Models covers it

How deep it goes
Defines command inputs and workflow placement, but defers chat configuration, compilation, and serving to subsequent commands.
Examples
Uses RedPajama INCITE Instruct 3B, q4f16_1 quantization, CUDA, and an MLC output directory.
What it assumes
Assumes cloned model weights, configuration files, Git LFS when needed, and an installed MLC LLM environment with device support.
What you can do after
Build it from scratch by converting cloned weights into device-targeted MLC artifacts for later compilation.
How it connects
Connects quantization, Hugging Face Hub weights, chat configuration, model compilation, and inference.
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