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 270M IT

OTel LLM 270M IT

by farbodtavakkoli

Open source · 669k downloads · 0 likes

0.0
(0 reviews)ChatAPI & Local
About

OTel LLM 270M IT is a language model specialized in the telecommunications sector, designed to meet the technical and regulatory needs of the industry. Trained on data from recognized sources such as 3GPP specifications, GSMA documents, and RFCs, it excels in analyzing and understanding complex technical documents related to networks, security, or domain standards. Its key capabilities include assisting in finding precise answers within technical knowledge bases and enhancing RAG (Retrieval-Augmented Generation) applications tailored for telecommunications. This model stands out for its sector-specific expertise, developed through collaboration with over 200 experts and major organizations in the field, ensuring heightened relevance and reliability for telecommunications professionals.

Documentation

OTel-LLM-270M-IT

OTel-LLM-270M-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 Modelgoogle/gemma-3-270m-it
Parameters270M
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
safetensorsgemma3_texttelecomtelecommunicationsgsmafine-tunedtext-generationconversationalen
Links & Resources
Specifications
CategoryChat
AccessAPI & Local
LicenseOpen Source
PricingOpen Source
Rating
0.0

Try OTel LLM 270M IT

Access the model directly