SACHS

Closed weights Massachusetts Institute of Technology (MIT),Stanford University 0.2K parameters April 2005

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
Massachusetts Institute of Technology (MIT),Stanford University
Organisation type
Academia,Academia
Country
United States of America
Published
22 April 2005
Authors
K. Sachs, O. Perez, D. Pe'er, D. A. Lauffenburger and G. P. Nolan

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Biology
Task
Other Biological 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
0.2K

From https://www.bnlearn.com/bnrepository/

Training data
5,400 tokens

I think? " The truncated singlecell data set (420 data points) shows a large (11-arc) decline in accuracy, missing more connections and reporting more unexplained arcs than its larger (5400 data points) counterpart (fig. S4B). " Seems potentially wrong by maybe 20%. Might need to add 1200.

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Citations
1,682

Sources

Where this record came from and when it was last checked.

Reference
Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data.
Last updated
28 November 2025

What the numbers mean

About this model

SACHS was published by Massachusetts Institute of Technology (MIT),Stanford University, in the country recorded as United States of America, during April 2005. The category the publisher falls under is academia,Academia.

It works in the domain of Biology, and is recorded as performing the task of other Biological Modeling.

This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.

Training and provenance

The training set ran to roughly 5,400 tokens of text.

Answers

SACHS — common questions

01

SACHS— how many parameters does it have?

It has a parameter count of 0.2K. From https://www.bnlearn.com/bnrepository/. 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.

02

SACHS— who created it?

It was published by Massachusetts Institute of Technology (MIT),Stanford University, based in United States of America, an organisation categorised as academia,Academia.

03

SACHS— when was it released?

It was published in April 2005. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

04

SACHS— what is it used for?

It works in the domain of Biology, and is recorded as handling the task of other Biological Modeling. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.

05

SACHS— 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.

06

SACHS— 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.

Source

Original publication

Record last updated 28 November 2025

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.