TSLM+MoS (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
- Tianjin University,Beijing Institute of Technology
- Organisation type
- Academia,Academia
- Country
- China
- Published
- 31 January 2019
- Authors
- Lipeng Zhang, Peng Zhang, Xindian Ma, Shuqin Gu, Zhan Su, Dawei Song
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling
- Numerical format
- FP32
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
- 9.1M
- Training data
- tokens
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)
no clear license https://github.com/TJUIRLAB/AAAI19-TSLM
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 21
- Benchmark data
- TSLM+MoS (WT2)
Sources
Where this record came from and when it was last checked.
- Reference
- A Generalized Language Model in Tensor Space
- Last updated
- 11 February 2026
What the numbers mean
About this model
TSLM+MoS (WT2) was published by Tianjin University,Beijing Institute of Technology, in China, in January 2019. academia,Academia is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
TSLM+MoS (WT2) — common questions
What GPU do I need to run TSLM+MoS (WT2)?
None. TSLM+MoS (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.
Is TSLM+MoS (WT2) open source?
No. TSLM+MoS (WT2) has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does TSLM+MoS (WT2) have?
TSLM+MoS (WT2) has 9.1M parameters. 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.
Who created TSLM+MoS (WT2)?
TSLM+MoS (WT2) was published by Tianjin University,Beijing Institute of Technology, based in China, categorised as academia,Academia.
When was TSLM+MoS (WT2) released?
TSLM+MoS (WT2) was published in January 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.
What is TSLM+MoS (WT2) used for?
TSLM+MoS (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.
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.