BTFBS
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
- Nanjing Agricultural University
- Organisation type
- Academia
- Country
- China
- Published
- 22 September 2024
- Authors
- Bingbing Jin, Song Liang, Xiaoqian Liu, Rui Zhang, Yun Zhu, Yuanyuan Chen, Guangjin Liu, Tao Yang
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Biology
- Task
- Protein-DNA binding prediction
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.
- Training data
- 10,333 tokens
"In order to ensure the consistency of sequence length, the maximum length of a DNA sequence is set to 100 and the maximum length of a protein sequence is set to 600. Sequences shorter than the maximum length are padded with zeros to match the fixed length." "As a result, 5159 non-redundant positive sequences are obtained. Approximately 10% of the sequences are randomly selected from the datasets as the independent dataset, while the remaining 90% of the sequences are used as the training and t…
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- BTFBS: binding-prediction of bacterial transcription factors and binding sites based on deep learning
- Last updated
- 28 November 2025
What the numbers mean
Background
BTFBS was published by Nanjing Agricultural University, in the country recorded as China, during September 2024. It comes out of an organisation categorised as academia.
It works in the domain of Biology, and is recorded as performing the task of protein-DNA binding prediction.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
How it was trained
It was trained on a corpus of about 10,333 tokens of text.
Answers
BTFBS — common questions
BTFBS— what is it used for?
It works in the domain of Biology, and is recorded as handling the task of protein-DNA binding prediction. These are the areas it was designed around; they describe intent rather than a hard boundary.
BTFBS— 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.
BTFBS— 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.
BTFBS— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
BTFBS— who created it?
It was published by Nanjing Agricultural University, based in China, an organisation categorised as academia.
BTFBS— when was it released?
It was published in September 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.