FinanceTabular data

AnomalyGFM

A pretrained model that finds anomalous nodes in a relationship graph and marks suspicious vertices on a new graph without training on it. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.

Developer
MaLA Lab, Singapore Management University (with University of Technology Sydney), Singapore
First release
Nov 2024
Latest release
Aug 2026
Sizes
weights file about 1.5 MB
License
Commercial use with conditionsno license stated in the repository — check with the authors
Running
On your own serverAlso runs without a GPU
Industries
Finance, Security, Science and research
Deploy on your server GitHub

What it does

  • Finding suspicious accounts and counterparties linked to each other
  • Highlighting atypical participants in a payment graph
  • Testing hypotheses about ring schemes and chains of intermediaries

Where it is used

Banks and payment servicesMarketplaces and classifieds platformsInternal control departments

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
fits
1 GPUOne GPU with 16–80 GB — mid-size versions
no versions
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. Обновление репозитория
  2. Препринт AnomalyGFM
  3. Код и веса на GitHub

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.

Frequently asked questions

Can AnomalyGFM be used in a commercial project?

With conditions. License: no license stated in the repository — check with the authors. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does AnomalyGFM need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does AnomalyGFM support Russian?

Language does not matter for this model: it does not work with text.

Where can I download AnomalyGFM and what does it cost?

The AnomalyGFM weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

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Details

Source: github.com/mala-lab/AnomalyGFM. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.