AI models
Multi-cell LSTM
Training compute
2×10¹⁵ FLOP
Parameters
7.2M
Published
Nov 15, 2018
Multi-cell LSTM is an AI model developed by University of Hyderabad (India), first published in November 2018. It works in the language domain, on tasks such as language modeling.
Training it took an estimated 2×10¹⁵ FLOP of compute (estimation method: operation counting). The model has 7,200,000 parameters. It was trained on roughly 929K datapoints.
Access: Unreleased. Its weights are not openly released. The reference paper has 6 citations. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- University of Hyderabad
- Country of organization
- India
- Domain
- Language
- Task
- Language modeling
- Training compute
- 2×10¹⁵ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 7,200,000
- Dataset size
- 929K
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 6
- Epoch confidence
- Likely
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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