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FlexMDM-Medium-BracketSAFE
dhruveshpatel/FlexMDM-Medium-BracketSAFE
FlexMDM-Medium-BracketSAFE is a machine learning model from dhruveshpatel. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Variable-length discrete diffusion model for bracket SAFE molecule generation.
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At a glance
- Access
- Public
- Created
- May 29, 2026
- Updated
- May 29, 2026
- SHA
- 7c33a922
Model card
From the Hugging Face model README
FlexMDM-Medium-BracketSAFE
Variable-length discrete diffusion model for bracket SAFE molecule generation.
Paper: https://arxiv.org/pdf/2602.18695
Training
| Hyperparameter | Value |
|---|---|
| Learning rate | 0.0001 |
| Global batch size | 2048 |
| Block size | 256 |
| Training steps | 50000 |
| Weight decay | 0.01 |
| Dataset | Bracket SAFE (datamol-io/safe-gpt, ~1.17B molecules) |
| Checkpoint | EMA weights at step 50000 |
W&B run: learned-noise-icml/safe_flexmdm_v2
Unconditional generation (de novo)
1024 sampling steps, 1000 molecules per run, mean ± std over 5 seeds (from paper Table 1 / appendix).
| conf. | p | Validity (%) | Diversity | Uniqueness (%) | Quality (%) |
|---|---|---|---|---|---|
| no | 98.900 ± 0.100 | 0.890 ± 0.000 | 99.600 ± 0.100 | 62.0 ± 0.7 | |
| yes | 67.800 ± 0.300 | 0.940 ± 0.000 | 61.700 ± 0.700 | 5.500 ± 0.400 |
Conditional generation (fragment-constrained)
Means over 5 runs (from paper Table 2). Tasks: LD (linker design), ME (motif extension), SD (scaffold decoration), SG (superstructure generation).
| Task | Validity (%) | Diversity | Uniqueness (%) | Quality (%) |
|---|---|---|---|---|
| Linker design | 99.7 | 0.599 | 63.7 | 50.8 |
| Motif extension | 99.7 | 0.623 | 79.9 | 46.9 |
| Scaffold decoration | 99.6 | 0.615 | 84.3 | 39.0 |
| Superstructure generation | 99.7 | 0.616 | 74.5 | 35.8 |
Usage
See the https://github.com/dhruvdcoder/LoFlexMDM release repository for training and evaluation instructions.
- Created
- May 29, 2026
- Updated
- May 29, 2026