| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - biology |
| - molecule-generation |
| - antimicrobial-peptides |
| - apexoracle |
| --- |
| |
| # ApexOracle guided-generation quickstart assets |
|
|
| This repository contains inference-only checkpoints and one BAA-3170 |
| genome/text condition bundle for the ApexOracle 256-step MIC+peptide guided |
| generation smoke test. |
|
|
| The three checkpoints preserve the deployed tensor state while omitting |
| optimizer state, training loops, callbacks, and the unused MIC classification |
| head. The condition bundle contains only the target used by the public smoke; |
| it does not redistribute the complete paper condition bank. |
|
|
| Use these files with the fixed ApexOracle super-repository and |
| `modules/generation/scripts/reproduce/run_paper_mic_peptide.py --asset-root`. |
| The smoke validates runtime and output contracts. A generated sample is not an |
| experimental activity result, and sampling is not bitwise deterministic on |
| CUDA. |
|
|
| See `manifest.json` for sizes, SHA-256 values, source-checkpoint provenance, |
| and the validated protocol. |
|
|
