RecommendersText

MiniOneRec

A small open generative recommender at 1.5B with published checkpoints and a full training pipeline. Handy as a learning and starter option; a real store needs fine-tuning on its own orders.

Developer
MiniOneRec open project, China
First release
Oct 2025
Latest release
Oct 2025
Sizes
1.5B
License
Commercial use allowedApache 2.0
Russian
Not supported
Running
On your own serverAlso runs without a GPU
Industries
Retail and marketplaces, Software development, Science and research
Deploy on your server Hugging Face GitHub

What it does

  • A quick recommendation prototype on your own data
  • Testing ideas before running a large model
  • Training a team to work with generative recommendations
  • Recommendations for a small catalogue

Where it is used

Online storesIT departments and contractorsResearch and training

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
fits
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. MiniOneRec: чекпойнты Industrial и Office на базе Qwen2.5-1.5B-Instruct

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 MiniOneRec 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 MiniOneRec 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 MiniOneRec support Russian?

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

Where can I download MiniOneRec and what does it cost?

The MiniOneRec 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.

Similar models

RecommendersOneRec (OpenOneRec)Kuaishou · ChinaCommercial use allowed

An open foundation model for recommendations from a short-video service: browsing and purchase history is fed to the model as a sequence and it predicts the next item or clip. Fine-tuning on your own data is required.

DetailsRecommendersHLLMByteDance · ChinaCommercial use with conditions

A two-level design: one language model reads the item description, the second builds the shopper interest from history. Ready checkpoints at 1B and 7B are published, but they need fine-tuning for your own catalogue.

DetailsRecommendersLC-RecRenmin University of China · ChinaCommercial use with conditions

An approach where every item gets a short identifier code that a language model understands, and the model predicts that code. Delta weights for three categories are published; no licence is stated on the card.

Details

Source: huggingface.co/kkknight/MiniOneRec. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.