RecommendersSearch and RAG

EasyRec (HKUDS)

Encoders that put a text portrait of a shopper and a text description of an item into one vector space so they can be matched directly. They help where a new listing has no purchase statistics yet.

The last open version came out in Aug 2024. The family has not been updated for a long time: the model still works, but do not expect fixes or new sizes.

Developer
HKUDS, University of Hong Kong, China
First release
Aug 2024
Latest release
Aug 2024
Sizes
three RoBERTa-based versions: small, base, large
License
Commercial use allowedApache 2.0
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

  • Recommendations for new items with no statistics
  • Matching by a text portrait of the shopper
  • Reinforcing ordinary recommendations with descriptions
  • Similar listings inside the catalogue

Where it is used

Online stores and marketplacesContent platformsMarketing 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. EasyRec-Small, EasyRec-Base, EasyRec-Large

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 EasyRec (HKUDS) be used in a commercial project?

Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does EasyRec (HKUDS) 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 EasyRec (HKUDS) support Russian?

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

Where can I download EasyRec (HKUDS) and what does it cost?

The EasyRec (HKUDS) 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/hkuds/easyrec-roberta-large. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.