File size: 1,037 Bytes
ebdc108 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 |
---
license: mit
language:
- en
---
# Evolla
<a href="https://doi.org/10.1101/2025.01.05.630192"><img src="https://img.shields.io/badge/Paper-bioRxiv-green" style="max-width: 100%;"></a>
<a href="https://x.com/duguyuan/status/1876446845951492221"><img src="https://img.shields.io/badge/Post-X-black" style="max-width: 100%;"></a>
A frontier protein-language generative model designed to decode the molecular language of proteins.
## Comparative analysis
In our paper, we conducted a comparative analysis against two state-of-the-art general-purpose language models: *Deepseek-v3* and *gpt-4o-2024-11-20*.
| **Model** | **Mean GPT score (± 95% confidence interval)** |
|-------------------------|-----------------------------|
| *Evolla* | 74.10 ± 0.81 |
| *Deepseek-v3* | 40.49 ± 0.56 |
| *gpt-4o-2024-11-20* | 37.07 ± 0.54 |
<img src="https://cdn-uploads.huggingface.co/production/uploads/643bb8ba6eeb746f5ad0a2db/k3WaRvNm_FDcF1ITWMQE6. |