by farbodtavakkoli
Open source · 782k downloads · 0 likes
OTel Embedding 300M is an embedding model specifically designed for the telecommunications sector, optimized to understand and process technical data related to industry standards and norms. Trained on reference documents such as 3GPP specifications, RFCs, and GSMA papers, it excels at semantically representing complex concepts in networking, security, and telecom APIs. Its primary applications include retrieval-augmented generation (RAG) systems and automated question-answering tools, enabling the extraction of precise information from specialized technical corpora. The model stands out for its fine-tuning on data validated by industry experts, ensuring heightened relevance for telecom professionals. It is part of a dedicated model collection, offering a consistent solution for artificial intelligence applied to the challenges of the telecom industry.
OTel-Embedding-300M 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 | google/Gemma3-Embedding-300M |
| Parameters | 300M |
| 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]