AI/EXPLORER
ToolsCategoriesSitesLLMsCompareAI QuizAlternativesPremium
—AI Tools
—Sites & Blogs
—LLMs & Models
—Categories
AI Explorer

Find and compare the best artificial intelligence tools for your projects.

Made within France

Explore

  • ›All tools
  • ›Sites & Blogs
  • ›LLMs & Models
  • ›Compare
  • ›Chatbots
  • ›AI Images
  • ›Code & Dev

Company

  • ›Premium
  • ›About
  • ›Contact
  • ›Blog

Legal

  • ›Legal notice
  • ›Privacy
  • ›Terms

© 2026 AI Explorer·All rights reserved.

HomeLLMsOTel LLM 8.3B Safety

OTel LLM 8.3B Safety

by farbodtavakkoli

Open source · 332k downloads · 0 likes

0.0
(0 reviews)ChatAPI & Local
About

OTel LLM 8.3B Safety is a language model specialized in the telecommunications sector, designed to meet the technical and regulatory needs of the industry. Trained on data from major standards and specifications such as those from GSMA, 3GPP, and O-RAN, it excels in analyzing and generating precise responses to complex topics related to networks, security, or APIs. Its primary applications include assisting telecom experts with question-answering tasks or integrating into augmented research systems (RAG) dedicated to this field. What sets it apart is its fine-tuning on corpora validated by hundreds of industry specialists, ensuring relevance and reliability tailored to the critical challenges of telecommunications. Ideal for professionals seeking to automate or optimize technical processes, it is part of a collection of open-source models dedicated to the telecom ecosystem.

Documentation

OTel-LLM-8.3B-Safety

OTel-LLM-8.3B-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 ModelEssentialAI/rnj-1-instruct
Parameters8.3B
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
pytorchgemma3_texttelecomtelecommunicationsgsmafine-tunedtext-generationconversationalen
Links & Resources
Specifications
CategoryChat
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Parameters3B parameters
Rating
0.0

Try OTel LLM 8.3B Safety

Access the model directly