by farbodtavakkoli
Open source · 1M downloads · 0 likes
OTel Embedding 33M is an embedding model specifically designed for the telecommunications sector, optimized to understand and process technical data related to industry norms and standards. It excels in information retrieval and question-answering applications, particularly for leveraging technical documents such as 3GPP specifications or RFCs. Trained on a diverse set of validated expert sources, it ensures precision tailored to industrial challenges. The model stands out for its ability to enhance Retrieval-Augmented Generation (RAG) systems in the telecom field, delivering more relevant results for sector professionals. It seamlessly integrates with the knowledge management and analytics tools used by telecommunications companies.
OTel-Embedding-33M 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 | BAAI/bge-small-en-v1.5 |
| Parameters | 33M |
| 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]