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How to smoke-test exported Evo VLM programs without weights with Evo VLM

Import the selected inference programs and check their interface on a CPU before any GPU setup.

  • Research
  • Intermediate
  • 15 minutes
  • From the README
  • Any agent

Who it is forA developer who wants to read the selected Qwen3-VL-2B inference programs and confirm they load before investing in a GPU environment.

The problemSetting up model weights and GPU dependencies is costly, so a developer needs a cheap way to confirm the exported programs are usable.

The outcomeThe developer sees the exported best_*.py programs import cleanly and their interface checks pass on CPU.

What you need first

  • Git and Python 3 installed locally
  • A clone of https://github.com/zzzz7788990213-ops/EvoVLM
  • For GPU inference only: a CUDA-capable GPU, PyTorch, Transformers, and the external Qwen model snapshots described in the runtime guide

Steps

  1. git clone https://github.com/zzzz7788990213-ops/EvoVLM.git
  2. cd EvoVLM/research/evolving-vlm-inference-main
  3. bash reproduce.sh smoke
  4. Open the selected best_*.py files in the same folder and read how each program builds its prompt, image preprocessing, and answer extraction.

Prompt for your agent

Clone https://github.com/zzzz7788990213-ops/EvoVLM and enter research/evolving-vlm-inference-main. Run `bash reproduce.sh smoke` and list each best_*.py file with whether it imports and passes the interface check. Verify that no model weights were loaded and no inference ran.

Caveat. The smoke check confirms that programs import and expose the expected interface, not that they answer charts correctly, which needs GPU inference with external model snapshots.

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