LSTM(medium)+Sememe+cell (WT2)

Closed weights Tsinghua University,Beijing University of Posts and Telecommunications,Huawei Noah's Ark Lab 24M parameters October 2019

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

" the “large” vanilla LSTM has much more parameters than “medium” LSTM+cell (76M vs. 24M), it is still outper- formed by the latter."

Training data
2,088,628 tokens
Epochs
40

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 China, in October 2019. It comes out of academia,Academia,Industry.

It works in Language, and is recorded as doing 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 about 2,088,628 tokens of text.

Answers

LSTM(medium)+Sememe+cell (WT2) — common questions

01

Is LSTM(medium)+Sememe+cell (WT2) open source?

No. LSTM(medium)+Sememe+cell (WT2) has not had its weights published, so it exists only as a service controlled by its owner.

02

How many parameters does LSTM(medium)+Sememe+cell (WT2) have?

LSTM(medium)+Sememe+cell (WT2) has 24M parameters. " 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.

03

Who created LSTM(medium)+Sememe+cell (WT2)?

LSTM(medium)+Sememe+cell (WT2) was published by Tsinghua University,Beijing University of Posts and Telecommunications,Huawei Noah's Ark Lab, based in China, categorised as academia,Academia,Industry.

04

When was LSTM(medium)+Sememe+cell (WT2) released?

LSTM(medium)+Sememe+cell (WT2) 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.

05

What is LSTM(medium)+Sememe+cell (WT2) used for?

LSTM(medium)+Sememe+cell (WT2) works in Language, and is recorded as handling 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.

06

What GPU do I need to run LSTM(medium)+Sememe+cell (WT2)?

None. LSTM(medium)+Sememe+cell (WT2) 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.

Source

Original publication

Record last updated 11 February 2026

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.