README.md
| 1 | --- |
| 2 | license: apache-2.0 |
| 3 | language: |
| 4 | - en |
| 5 | base_model: |
| 6 | - EssentialAI/rnj-1-instruct |
| 7 | tags: |
| 8 | - telecom |
| 9 | - telecommunications |
| 10 | - gsma |
| 11 | - fine-tuned |
| 12 | pipeline_tag: text-generation |
| 13 | --- |
| 14 | |
| 15 | # OTel-LLM-8.3B-IT |
| 16 | |
| 17 | **OTel-LLM-8.3B-IT** is a telecom-specialized language model fine-tuned on telecommunications domain data. It is part of the [OTel Family of Models](https://huggingface.co/collections/farbodtavakkoli/otel-llm), an open-source initiative to build industry-standard AI models for the global telecommunications sector. |
| 18 | |
| 19 | ## Model Details |
| 20 | |
| 21 | | Attribute | Value | |
| 22 | |-----------|-------| |
| 23 | | **Base Model** | [EssentialAI/rnj-1-instruct](https://huggingface.co/EssentialAI/rnj-1-instruct) | |
| 24 | | **Parameters** | 8.3B | |
| 25 | | **Training Method** | Full parameter fine-tuning | |
| 26 | | **Language** | English | |
| 27 | | **License** | Apache 2.0 | |
| 28 | |
| 29 | ## Training Data |
| 30 | |
| 31 | The model was trained on telecom-focused data curated by 100+ domain experts. Each source class was contributed by a specific institutional partner: |
| 32 | |
| 33 | | Source | Contributor | |
| 34 | |---|---| |
| 35 | | arXiv telecom papers, 3GPP standards, telecom Wikipedia, telecom Common Crawl | Yale University | |
| 36 | | GSMA Permanent Reference Documents, Discover portal | GSMA | |
| 37 | | IETF RFC series | NetoAI | |
| 38 | | Industry whitepapers | Khalifa University | |
| 39 | | O-RAN specifications (working groups 1, 2, 4, 5, 6, 7, 8, 9, 10) | University of Leeds | |
| 40 | | O-RAN documents across working groups | The University of Texas at Dallas | |
| 41 | |
| 42 | Released datasets: [OTel-LLM](https://huggingface.co/datasets/farbodtavakkoli/OTel-LLM), [OTel-Embedding](https://huggingface.co/datasets/farbodtavakkoli/OTel-Embedding), [OTel-Reranker](https://huggingface.co/datasets/farbodtavakkoli/OTel-Reranker), [OTel-Safety](https://huggingface.co/datasets/farbodtavakkoli/OTel-Safety). |
| 43 | |
| 44 | ## Intended Use |
| 45 | |
| 46 | The OTel model family is designed to power end-to-end Retrieval-Augmented Generation (RAG) pipelines for telecommunications. The three model types serve complementary roles: |
| 47 | |
| 48 | 1. **Embedding** — Retrieve relevant chunks from telecom specifications, standards, and documentation. |
| 49 | 2. **Reranker** — Re-score and prioritize the retrieved chunks for relevance. |
| 50 | 3. **LLM** — Generate accurate responses grounded in the retrieved context. |
| 51 | |
| 52 | Users can deploy the full pipeline or use individual models independently based on their needs. |
| 53 | |
| 54 | **Note:** The LLMs include abstention training — if the model does not receive sufficient context, it will decline to answer rather than hallucinate. This means the models are optimized for context-grounded generation, not open-ended question answering. |
| 55 | |
| 56 | ## Related Models |
| 57 | |
| 58 | ### Language Models |
| 59 | - [OTel LLM Collection](https://huggingface.co/collections/farbodtavakkoli/otel-llm) |
| 60 | |
| 61 | ### Embedding Models |
| 62 | - [OTel Embedding Collection](https://huggingface.co/collections/farbodtavakkoli/otel-embedding) |
| 63 | |
| 64 | ### Reranker Models |
| 65 | - [OTel Reranker Collection](https://huggingface.co/collections/farbodtavakkoli/otel-reranker) |
| 66 | |
| 67 | ## Related Datasets |
| 68 | |
| 69 | - [OTel-Embedding](https://huggingface.co/datasets/farbodtavakkoli/OTel-Embedding) |
| 70 | - [OTel-Safety](https://huggingface.co/datasets/farbodtavakkoli/OTel-Safety) |
| 71 | - [OTel-LLM](https://huggingface.co/datasets/farbodtavakkoli/OTel-LLM) |
| 72 | - [OTel-Reranker](https://huggingface.co/datasets/farbodtavakkoli/OTel-Reranker) |
| 73 | |
| 74 | ## Training Infrastructure |
| 75 | |
| 76 | - **Framework**: ScalarLM (GPU-agnostic) |
| 77 | - **Compute**: AMD and NVIDIA GPUs. |
| 78 | |
| 79 | ## Project Resources |
| 80 | |
| 81 | - **Project page:** https://huggingface.co/farbodtavakkoli |
| 82 | - **Code:** https://github.com/farbodtavakkoli/OTel |
| 83 | - **Media coverage list:** https://github.com/farbodtavakkoli/OTel/blob/main/docs/media_coverage.md |
| 84 | |
| 85 | ## Citation |
| 86 | |
| 87 | |
| 88 | ```bibtex |
| 89 | @misc{otel_models_2026, |
| 90 | title = {OTel: Open Telco AI Datasets, Benchmarks, and Models}, |
| 91 | author = {Tavakkoli, Farbod and others}, |
| 92 | year = {2026}, |
| 93 | note = {Open Telco (OTel) model release}, |
| 94 | url = {https://huggingface.co/farbodtavakkoli} |
| 95 | } |
| 96 | ``` |
| 97 | |
| 98 | ## Contact |
| 99 | |
| 100 | If you have any technical questions, please feel free to reach out to farbod.tavakkoli@att.com or farbodtavakoli@gmail.com |
| 101 | |