by farbodtavakkoli
Open source · 334k downloads · 0 likes
OTel Embedding 4B is a specialized embedding model designed for the telecommunications sector, optimized to understand and process technical data related to industry standards and norms. It excels in information retrieval and question-answering applications, particularly for leveraging technical documents such as 3GPP specifications, RFCs, or O-RAN documents. Trained on data validated by over 200 industry experts, it delivers precision tailored to the needs of telecom professionals. The model stands out for its ability to generate semantically relevant representations for use cases like technical document analysis or automated assistance in network management. It seamlessly integrates into Retrieval-Augmented Generation (RAG) solutions to enhance the efficiency of AI systems dedicated to telecommunications.
OTel-Embedding-4B is a telecom-specialized embedding model fine-tuned on telecommunications domain data. It is part of the OTel Family of Models, an open-source initiative to build industry-standard AI models for the global telecommunications sector.
| Attribute | Value |
|---|---|
| Base Model | Qwen/Qwen3-Embedding-4B |
| Parameters | 4B |
| Training Method | Full parameter fine-tuning |
| Language | English |
| License | Apache 2.0 |
The model was trained on high-quality telecom-focused data curated by 200+ domain experts from organizations including AT&T, RelationalAI, AMD, GSMA, Purdue University, Khalifa University, University of Leeds, Yale University, The University of Texas at Dallas, NetoAI, and MantisNLP.
Data Sources:
This model is optimized for:
@misc{otel2026,
title={OTel: Open Telco AI Models},
author={Tavakkoli, Farbod and Diamos, Gregory and Paulk, Roderic and Terrazas, Jorden},
year={2026},
url={https://huggingface.co/farbodtavakkoli}
}
If you have any technical questions, please feel free to reach out to [email protected] or [email protected]