Documents and OCRText analysis

LiLT

A light model that takes both the text and the position of blocks on the page into account: trained in one language and transferable to others. Good for tagging fields in resumes and forms. A human makes the decision about a candidate; automatic screening without review must not be used.

The last open version came out in Oct 2022. The family has not been updated for a long time: the model still works, but do not expect fixes or new sizes.

Developer
SCUT DLVC Lab, South China University of Technology, China
First release
Sep 2022
Latest release
Oct 2022
Sizes
about 130M for the English version and about 280M for the multilingual one
License
Commercial use allowedMIT
Russian
Not stated
Running
On your own serverAlso runs without a GPU
Industries
Documents and accounting, HR, Finance
Deploy on your server Hugging Face GitHub

What it does

  • Tagging fields in resumes and forms
  • Extracting data from forms and templates
  • Parsing documents in several languages

Where it is used

HR and recruitingDocument workflowsFinance 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. LiLT-InfoXLM-base, многоязычная
  2. LiLT-RoBERTa-en-base

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 LiLT be used in a commercial project?

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

What hardware does LiLT 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 LiLT support Russian?

The model card does not list languages, so Russian support cannot be promised — it has to be tested on your own examples.

Where can I download LiLT and what does it cost?

The LiLT 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/SCUT-DLVCLab/lilt-roberta-en-base. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.