ConTeXT-Skill-Extraction
Finds mentions of skills in a vacancy or resume text and maps them to the company skill reference list. A human makes the decision about a candidate; automatic screening without review must not be used.
- Developer
- TechWolf, Belgium
- First release
- Dec 2024
- Latest release
- Dec 2024
- Sizes
- 109M
- License
- Commercial use with conditionsno license is stated on the model card — check with the developer
- Russian
- Not supported
- Running
- On your own serverAlso runs without a GPU
- Industries
- HR, Education
What it does
- Extracting skills from a job description
- Matching candidate skills against requirements
- Building a competence map across departments
Where it is used
Hardware requirements
Versions
- ConTeXT-Skill-Extraction-base
How to run it
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 ConTeXT-Skill-Extraction be used in a commercial project?
With conditions. License: no license is stated on the model card — check with the developer. Restrictions vary — region, company revenue, attribution requirements. Have a lawyer check the terms before a commercial launch.
What hardware does ConTeXT-Skill-Extraction 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 ConTeXT-Skill-Extraction support Russian?
No. The developer documentation lists the supported languages and Russian is not among them.
Where can I download ConTeXT-Skill-Extraction and what does it cost?
The ConTeXT-Skill-Extraction 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
- SelectionI pick the model size for your task and hardware and test it on your examples.
- DeploymentI deploy it on your server or in a closed network and provide an API.
- Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
- IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.
Similar models
A model from a Belgian HR company: it turns job titles into vectors so you can find similar vacancies and resumes. A human makes the decision about a candidate; automatic screening without review must not be used.
DetailsText analysisESCOXLM-R и JobBERT (ITU Copenhagen)Mike Zhang, Rob van der Goot, Barbara Plank (IT University of Copenhagen and LMU Munich) · DenmarkCommercial use with conditionsA research line of models for labour market texts: trained on job postings and the European ESCO occupation taxonomy, they pull skills and requirements out of vacancies. A human makes the decision about a candidate; automatic screening without review must not be used.
DetailsText analysisGLiNERUrchade Zaratiana and Fastino AI · France / USACommercial use allowedFinds the entities you need in text without training: just list what to look for (name, amount, date). GLiNER2 also classifies text. Multilingual versions understand Russian.
DetailsSource: huggingface.co/TechWolf/ConTeXT-Skill-Extraction-base. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.


