Update card: att links, resources, citation, contact
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README.md
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# OTel-LLM-8.3B-Classification
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**OTel-LLM-8.3B-Classification** is a telecom-specialized classification model fine-tuned for **5G network root cause analysis (RCA)**, achieving **~99% accuracy** on the [TeleLogs benchmark](https://huggingface.co/datasets/netop/TeleLogs). It is part of the [OTel Family of Models](https://huggingface.co/collections/
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## Model Details
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## Related Models
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### Language Models
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- [OTel LLM Collection](https://huggingface.co/collections/
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### Embedding Models
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- [OTel Embedding Collection](https://huggingface.co/collections/
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### Reranker Models
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- [OTel Reranker Collection](https://huggingface.co/collections/
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## Related Datasets
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- [TeleLogs](https://huggingface.co/datasets/netop/TeleLogs) — 5G RCA benchmark
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- [OTel-Embedding](https://huggingface.co/datasets/
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- [OTel-Safety](https://huggingface.co/datasets/
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- [OTel-LLM](https://huggingface.co/datasets/
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- [OTel-Reranker](https://huggingface.co/datasets/
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## Training Infrastructure
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- **Framework**: ScalarLM (GPU-agnostic)
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- **Compute**: TensorWave with AMD GPUs and Azure with NVIDIA GPUs
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- **Training Code**: [
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## Citation
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```bibtex
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@inproceedings{tavakkoli2026otel,
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title = {OTel: Open Telco AI Datasets, Benchmarks, and Models},
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author = {Tavakkoli, Farbod and
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booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track},
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year = {2026},
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url = {https://github.com/farbodtavakkoli/OTel}
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# OTel-LLM-8.3B-Classification
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**OTel-LLM-8.3B-Classification** is a telecom-specialized classification model fine-tuned for **5G network root cause analysis (RCA)**, achieving **~99% accuracy** on the [TeleLogs benchmark](https://huggingface.co/datasets/netop/TeleLogs). It is part of the [OTel Family of Models](https://huggingface.co/collections/att/otel-10-llm), an open-source initiative to build industry-standard AI models for the global telecommunications sector.
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## Model Details
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## Related Models
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### Language Models
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- [OTel LLM 2.0 Collection](https://huggingface.co/collections/att/otel-20-llm)
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- [OTel LLM 1.0 Collection](https://huggingface.co/collections/att/otel-10-llm)
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### Embedding Models
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- [OTel Embedding Collection](https://huggingface.co/collections/att/otel-10-embedding)
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### Reranker Models
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- [OTel Reranker Collection](https://huggingface.co/collections/att/otel-10-reranker)
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## Related Datasets
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- [TeleLogs](https://huggingface.co/datasets/netop/TeleLogs) — 5G RCA benchmark
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- [OTel-Embedding](https://huggingface.co/datasets/att/OTel-Embedding)
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- [OTel-Safety](https://huggingface.co/datasets/att/OTel-Safety)
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- [OTel-LLM](https://huggingface.co/datasets/att/OTel-LLM)
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- [OTel-Reranker](https://huggingface.co/datasets/att/OTel-Reranker)
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## Training Infrastructure
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- **Framework**: ScalarLM (GPU-agnostic)
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- **Compute**: TensorWave with AMD GPUs and Azure with NVIDIA GPUs
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- **Training Code**: [OTel code](https://github.com/farbodtavakkoli/OTel)
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## Resources
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- [Project Page](https://huggingface.co/att)
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- [OTel code](https://github.com/farbodtavakkoli/OTel)
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- [OTel Selected Coverage](https://github.com/farbodtavakkoli/OTel/blob/main/docs/OTel-selected-coverage.md)
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- [OTel Paper](https://arxiv.org/pdf/2610.07766)
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- [OTel 1.0 Coverage](https://github.com/farbodtavakkoli/OTel/blob/main/docs/OTel-1.0-coverage.md)
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- [OTel 2.0 Coverage](https://github.com/farbodtavakkoli/OTel/blob/main/docs/OTel-2.0-coverage.md)
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## Citation
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```bibtex
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@inproceedings{tavakkoli2026otel,
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title = {OTel: Open Telco AI Datasets, Benchmarks, and Models},
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author = {Tavakkoli, Farbod and others},
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booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track},
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year = {2026},
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url = {https://github.com/farbodtavakkoli/OTel}
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