Practical overview
When it fits
Use Gen.jl when a Julia project needs probabilistic model-building with programmable inference.
Who it is for
- Julia developers building probabilistic models.
- People creating tutorials and examples of probabilistic programming workflows.
Documented uses
- Build probabilistic models in Julia.
- Write programmable inference algorithms for those models.
- Create tutorials and examples that demonstrate Gen.jl workflows.
Requirements & limits
- Gen.jl is a Julia library, and installation is through Julia’s package manager.
- The listed platforms are Linux, macOS and Windows.
- The project is a developer tool for models and inference, rather than a hosted application.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install Gen.jl and check the local installation
Add Gen.jl with Julia's package manager, load it, and run its package tests.
Before you start
- Julia REPL with Julia's package manager.
Steps
In the Julia REPL, type
]to enter Pkg REPL mode.Run
add Gento install the package. For the latest development version instead, runadd https://github.com/probcomp/Gen.jl.git.Return to the Julia REPL or add
using Genat the top of a script to use the package.To test the installation locally, run
using Pkg; Pkg.test("Gen").
Expected outcome
Gen.jl is installed and can be loaded in the Julia REPL or a script; the documented local test command is available.
Guide limitations
- This guide covers installation and the local test command, not building a probabilistic model or running an inference workflow.
Compare options for Model inference and serving
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Gen.jl | Build probabilistic models in Julia. | Linux, macOS, Windows | |
| Hyperpose | Customize pose-estimation architectures and datasets. | Docker, Linux, macOS, Windows | |
| Multi Task Nlp | Define multiple tasks and their data and model settings in a YAML file. | Linux, macOS, Windows | The project is an open-source library under the Apache-2.0 license, distributed through its public GitHub repository. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 11 October 2026
- Original website title
- GitHub - probcomp/Gen.jl: A general-purpose probabilistic programming system with programmable inference · GitHub · Official homepage title · retained in its source language

