YuYan 11B
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
- Hong Kong Baptist University,NetEase
- Organisation type
- Academia,Industry
- Country
- Hong Kong, China
- Published
- 15 July 2022
- Authors
- Gongzheng Li, Yadong Xi, Jingzhen Ding, Duan Wang, Ziyang Luo, Rongsheng Zhang, Bai Liu, Changjie Fan, Xiaoxi Mao, Zeng Zhao
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
- Approach
- Self-supervised learning
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
- 11B
- Training data
- tokens
https://huggingface.co/FUXI/yuyan-11b
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA A100 PCIe,NVIDIA GeForce RTX 2080 Ti 11GB
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Likely above 10²³ FLOP
- Yes
- Record confidence
- Confident
- Citations
- 11
Sources
Where this record came from and when it was last checked.
- Reference
- Easy and Efficient Transformer: Scalable Inference Solution For Large NLP Model
- Last updated
- 1 December 2025
What the numbers mean
About this model
YuYan 11B was published by Hong Kong Baptist University,NetEase, in the country recorded as Hong Kong, during July 2022. The publishing organisation is categorised as academia,Industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
YuYan 11B — common questions
YuYan 11B— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
YuYan 11B— how many parameters does it have?
It has a parameter count of 11B. https://huggingface.co/FUXI/yuyan-11b. 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.
YuYan 11B— who created it?
It was published by Hong Kong Baptist University,NetEase, based in Hong Kong, an organisation categorised as academia,Industry.
YuYan 11B— when was it released?
It was published in July 2022. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
YuYan 11B— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
YuYan 11B— 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.