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beeFormer

Description encoders trained so that items people actually buy together end up close to each other, not merely items that sound alike. Versions trained on public catalogues are published.

Developer
Recombee, Czechia
First release
Aug 2024
Latest release
Sep 2024
Sizes
about 110M (built on all-mpnet-base-v2)
License
Commercial use with conditionsLlama 3.1 Community License - the training texts were produced with Llama 3.1; the repository code is under CC BY-SA 4.0
Russian
Not supported
Running
On your own serverAlso runs without a GPU
Industries
Retail and marketplaces, Media and production, Marketing and content
Deploy on your server Hugging Face GitHub

What it does

  • A frequently-bought-together block
  • Recommendations for listings with no sales history
  • Moving the model to a new catalogue
  • Similar items by description

Where it is used

Online storesMedia libraries and book cataloguesMarketing and curated lists

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 карточек моделей
  2. Llama-movielens-mpnet, Llama-goodbooks-mpnet, Llama-amazbooks-mpnet, Llama-goodlens-mpnet

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.Hugging Face
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 beeFormer be used in a commercial project?

With conditions. License: Llama 3.1 Community License - the training texts were produced with Llama 3.1; the repository code is under CC BY-SA 4.0. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.

What hardware does beeFormer 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 beeFormer support Russian?

No. The developer documentation lists the supported languages and Russian is not among them.

Where can I download beeFormer and what does it cost?

The beeFormer 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: huggingface.co/beeformer/Llama-movielens-mpnet. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.