HyPLM Technical Report
- Published
- Source
- arXiv
- Paper number
- 1450
- Field
- Machine Learning
- arXiv ID
- 2611.12000
Key points
- HyPLM-Flash is a 650M-parameter masked language model trained on 726 billion tokens, 0.73 times the data of ESM-2 650M and a fifth to an eighth of that of E1-600M and ESM C 600M.
- It reached a ProteinGym zero-shot Spearman correlation of 0.409, statistically tied with ESM-2 650M, ESM C 600M, and E1-600M, and scored highest on organismal fitness among self-supervised single-sequence models.
- Its long-range contact precision at L/5 on ProteinNet was 0.650 against 0.392 for ESM-2 650M, the best of all evaluated models including ESM-2 15B.
- With fused kernels and INT8 matrix multiplication, the inference engine embeds about 130,000 residues per second on a single H20 GPU, 1.9 to 2.7 times faster than other 600M-class encoders.
- The model was trained by Hyra 2.0, the research agent developed by the team, and the weights and inference engine were released.
Paper links
External research summaries. These are not HDATF publications or measured product results.