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HomeLLMsOTel LLM 12B Safety

OTel LLM 12B Safety

by farbodtavakkoli

Open source · 159k downloads · 0 likes

0.0
(0 reviews)ChatAPI & Local
About

OTel LLM 12B Safety is a specialized language model tailored for the telecommunications sector, designed to meet the technical and regulatory demands of the industry. Fine-tuned using data validated by over 200 domain experts, it excels in analyzing and generating precise responses on topics such as 3GPP standards, O-RAN specifications, or network security protocols. Its primary purpose is to enhance research applications through retrieval-augmented generation (RAG) and automated question-answering systems, leveraging reliable sources like GSMA documents or RFCs. What sets it apart is its ability to interpret complex industry concepts while ensuring alignment with industrial standards. Ideal for telecom operators, equipment manufacturers, or researchers, it accelerates the understanding of regulations and technical best practices.

Documentation

OTel-LLM-12B-Safety

OTel-LLM-12B-Safety is a telecom-specialized language 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.

Model Details

AttributeValue
Base Modelgoogle/gemma-3-12b-it
Parameters12B
Training MethodFull parameter fine-tuning
LanguageEnglish
LicenseApache 2.0

Training Data

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:

  • GSMA Permanent Reference Documents
  • 3GPP Specifications
  • O-RAN Documentation
  • RFC Series
  • eSIM, terminals, security, networks, roaming, APIs
  • Industry whitepapers and telecom academic papers

Intended Use

This model is optimized for:

  • RAG applications in telecommunications
  • Question answering on telecom specifications and standards

Related Models

Language Models

  • OTel LLM Collection

Embedding Models

  • OTel Embedding Collection

Reranker Models

  • OTel Reranker Collection

Related Datasets

  • OTel-Embedding
  • OTel-Safety
  • OTel-LLM
  • OTel-Reranker

Training Infrastructure

  • Framework: ScalarLM (GPU-agnostic)
  • Compute: TensorWave with AMD GPUs and Azure with NVIDIA GPUs.

Citation

Bibtex
@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}
}

Contact

If you have any technical questions, please feel free to reach out to [email protected] or [email protected]

Capabilities & Tags
pytorchgemma3telecomtelecommunicationsgsmafine-tunedtext-generationconversationalen
Links & Resources
Specifications
CategoryChat
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Parameters12B parameters
Rating
0.0

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