AI models
Lightweight Fine-tuning a Pretrained Protein Language Model for Protein Secondary
Training compute
1.9×10²² FLOP
Published
Mar 23, 2023
Lightweight Fine-tuning a Pretrained Protein Language Model for Protein Secondary is an AI model developed by Henan University (China), first published in March 2023. It works in the biology domain, on tasks such as protein or nucleotide language model (plm/nlm) and protein folding prediction.
Training it took an estimated 1.9×10²² FLOP of compute (estimation method: hardware). It was trained on roughly 10M datapoints. Training ran on 1 NVIDIA GeForce RTX 3090 Ti for about 27 hours.
It is built on top of ProtT5-XL-U50. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Henan University
- Country of organization
- China
- Domain
- Biology
- Task
- Protein or nucleotide language model (pLM/nLM), Protein folding prediction
- Training compute
- 1.9×10²² FLOP
- Compute estimation method
- Hardware
- Dataset size
- 10M
- Training hardware
- NVIDIA GeForce RTX 3090 Ti
- Chips used
- 1
- Training time
- 27 h
- Training power draw
- 493 W
- Base model
- ProtT5-XL-U50
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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