LSTM(medium)+Sememe+cell (WT2)
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Tsinghua University,Beijing University of Posts and Telecommunications,Huawei Noah's Ark Lab
- Organisation type
- Academia,Academia,Industry
- Country
- China
- Published
- 20 October 2019
- Authors
- Yujia Qin, Fanchao Qi, Sicong Ouyang, Zhiyuan Liu, Cheng Yang, Yasheng Wang, Qun Liu, Maosong Sun
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 24M
- Training data
- 2,088,628 tokens
- Epochs
- 40
" the “large” vanilla LSTM has much more parameters than “medium” LSTM+cell (76M vs. 24M), it is still outper- formed by the latter."
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Open (non-commercial)
code for Wikitext/PTB. no license. https://github.com/thunlp/SememeRNN/blob/master/LM/main.py
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Benchmark data
- LSTM(medium)+Sememe+cell
Sources
Where this record came from and when it was last checked.
- Reference
- Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes
- Last updated
- 11 February 2026
What the numbers mean
Background
LSTM(medium)+Sememe+cell (WT2) was published by Tsinghua University,Beijing University of Posts and Telecommunications,Huawei Noah's Ark Lab, in the country recorded as China, during October 2019. It comes out of an organisation categorised as academia,Academia,Industry.
It works in the domain of Language, and is recorded as performing the task of language modeling.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
What went into building it
It was trained on a corpus of about 2,088,628 tokens of text.
Answers
LSTM(medium)+Sememe+cell (WT2) — common questions
LSTM(medium)+Sememe+cell (WT2)— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
LSTM(medium)+Sememe+cell (WT2)— how many parameters does it have?
It has a parameter count of 24M. " the “large” vanilla LSTM has much more parameters than “medium” LSTM+cell (76M vs. 24M), it is still outper- formed by the latter.". That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
LSTM(medium)+Sememe+cell (WT2)— who created it?
It was published by Tsinghua University,Beijing University of Posts and Telecommunications,Huawei Noah's Ark Lab, based in China, an organisation categorised as academia,Academia,Industry.
LSTM(medium)+Sememe+cell (WT2)— when was it released?
It was published in October 2019. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
LSTM(medium)+Sememe+cell (WT2)— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
LSTM(medium)+Sememe+cell (WT2)— what GPU do I need to run it?
None. This is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.