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Decision brief
LLM-VM is a Python-based repository aimed at LLM development, highlighting tools for distillation, training, and inference.
Good fit when
- When you need streamlined processes for model distillation in your project.
- If rapid prototyping with local LLM deployment aligns with your goals.
Avoid when
- Avoid if strict adherence to responsible AI principles is a requirement.
- Not recommended for large-scale commercial deployments that necessitate stable and thoroughly validated tools.
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (832d since push)
- As of today
- Provenance
- Not a fork · Organization account
- As of today
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install LLM-VMSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A Python-based repository for LLM development, offering tools for distillation, training, and inference.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 25, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 25, 2026
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Aug 25, 2026
- Languages
- python
Source: github.language+pyproject.toml · Aug 25, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 25, 2026)
Python >=3.10 Supported. Older versions of Python are on a best-effort basis.Source link
Tags
README
🥹 Requirements
Installation Requirements
Python >=3.10 Supported. Older versions of Python are on a best-effort basis.
Use bash > python3 --version to check what version you are on.
To upgrade your python, either create a new python env using bash > conda create -n myenv python=3.10 or go to https://www.python.org/downloads/ to download the latest version.
If you plan on running the setup steps below, a proper Python version will be installed for you
System Requirements
Different models have different system requirements. Limiting factors on most systems will likely be RAM, but many functions will work at even 16 GB of RAM.
That said, always lookup the information about the models you're using, they all have different sizes and requirements in memory and compute resources.
👨💻 Installation
The quickest way to get started is to run pip install llm-vm in your Python environment.
Another way to install the LLM-VM is to clone this repository and install it with pip like so:
> git clone https://github.com/anarchy-ai/LLM-VM.git
> cd LLM-VM
> ./setup.sh
The above bash script setup.sh only works for MacOS and Linux.
Alternatively you could do this:
> git clone https://github.com/anarchy-ai/LLM-VM.git
> cd LLM-VM
> python -m venv <name>
> source <name>/bin/activate
> python -m pip install -e ."[dev]"
If you are on Windows. You can follow either of the below two methods:
Before doing any of the following steps, you have to first open Powershell as administrator and run the below command
> Set-ExecutionPolicy RemoteSigned
> Press Y and enter
> exit
Now you can follow either of the below two methods:
- Open Powershell and do this:
> git clone https://github.com/anarchy-ai/LLM-VM.git
> cd LLM-VM
> .\windows_setup.ps1
or
- Open Powershell and do this:
> winget install Python.Python.3.11
> python --version
> git clone https://github.com/anarchy-ai/LLM-VM.git
> cd LLM-VM
> python -m venv anarchyai
> anarchyai\Scripts\activate
> python -m pip install -e .
Note:
- For the above steps to work you have to be on Windows 10 1709 (build 16299) or later build.
- Enable developer mode in windows settings(not compulsory but if enabled will give an added advantage)
One Last Step, almost there!
If you're using one of the OpenAI models, you will need to set the LLM_VM_OPENAI_API_KEY environment
variable with your API key.
For agents
This page has a .md twin and JSON over the API.