DEPLOYMENT.md

Hugging Face migration notes

This repository was pulled from:

• source Space: https://huggingface.co/spaces/ChemFM/MaterialInverseDesignDemo

Target destination:

• destination org: https://huggingface.co/aim4composites

What changed for GPU hosting

• README front matter now recommends suggested_hardware: t4-small
• spaces is kept in requirements.txt so ZeroGPU can allocate GPU time through @spaces.GPU
• the app text now describes the Space as compatible with both ZeroGPU and dedicated GPU hardware
• runtime knobs were added so the thermoforming step can be tuned without code edits:
  • MG_DEFAULT_N_GENERATE
  • MG_MAX_GENERATE
  • MG_THERMO_RESTARTS
  • MG_THERMO_EPOCHS

Recommended Hugging Face Space settings

1. Create a new Gradio Space under aim4composites.
2. Push this repository to that new Space.
3. In the Space hardware settings, choose either ZeroGPU or Nvidia T4 small.
4. Leave storage at the default unless larger artifacts are added later.
5. Restart the Space and verify generation completes. On Nvidia T4 small, logs should show CUDA is available. On ZeroGPU, CUDA is allocated when the decorated generation function runs.

Suggested first validation pass

1. Open the Space and load the default test condition.
2. Run material inverse design with the default 3 candidates.
3. Select the top-ranked design.
4. Run thermoforming once with a small target example.
5. Confirm:
   • the app starts successfully
   • candidate generation completes
   • thermoforming completes
   • no out-of-memory or timeout errors appear in the logs

Optional runtime tuning if the Space feels slow

Set these Space variables:

• MG_DEFAULT_N_GENERATE=2
• MG_MAX_GENERATE=4
• MG_THERMO_RESTARTS=6
• MG_THERMO_EPOCHS=300

If runtime remains comfortably fast, increase these gradually.