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HomeLLMsOTel LLM 32B IT

OTel LLM 32B IT

by farbodtavakkoli

Open source · 86k downloads · 0 likes

0.0
(0 reviews)ChatAPI & Local
About

OTel LLM 32B IT is a language model specialized in the telecommunications sector, designed to meet the technical and operational needs of the industry. Trained on high-quality data from recognized standards and specifications such as those from GSMA, 3GPP, or O-RAN, it excels in understanding and analyzing complex technical documents. Its core capabilities include processing question-answer tasks on telecom standards, as well as integration into retrieval-augmented generation (RAG) applications to streamline access to specialized information. The model stands out for its industry-specific expertise, developed in collaboration with over 200 experts and major organizations in the field. It is particularly aimed at telecom professionals, developers, and researchers seeking to automate or optimize tasks related to infrastructure, protocols, or technological innovations in the sector.

Documentation

OTel-LLM-32B-IT

OTel-LLM-32B-IT 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 Modelallenai/OLMo-3-32B
Parameters32B
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
pytorcholmo3telecomtelecommunicationsgsmafine-tunedtext-generationconversationalen
Links & Resources
Specifications
CategoryChat
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Parameters32B parameters
Rating
0.0

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