wehub-resource-sync
27 lines
972 B
ReStructuredText
27 lines
972 B
ReStructuredText
.. _finetune_agent:
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================================
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FT-Agent for LLM Fine-Tuning
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================================
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FT-Agent is the RD-Agent scenario for autonomous LLM fine-tuning, introduced in
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the ICML 2026 paper `FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language
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Agents <https://arxiv.org/abs/2603.01712>`_.
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The scenario automates benchmark-driven data processing, LLaMA-Factory training
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configuration, fail-fast validation, OpenCompass evaluation, and feedback-based
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iteration.
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The full user guide is maintained in the repository:
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`rdagent/app/finetune/llm/README.md <https://github.com/microsoft/RD-Agent/blob/main/rdagent/app/finetune/llm/README.md>`_
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Minimal command after configuring the required ``FT_*`` settings:
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.. code-block:: sh
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rdagent llm_finetune --base-model Qwen/Qwen2.5-7B-Instruct
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Please read the full guide before running this scenario. A first run can download
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large dataset/model assets and consume LLM API calls and GPU hours.
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