att/OTel-Embedding-34M
feature-extraction model by att
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Model card & documentation
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OTel-Embedding-34M is a telecom embedding model full-parameter fine-tuned on OTel telecommunications data. It is part of the OTel Family of Models, an open-source initiative to build reference AI resources for the global telecommunications sector. Across the 10 OTel embedding baselines, OTel fine-tuning improves telecom retrieval quality by +9.2 to +59.7 NDCG@10 percentage points. As of May 3, 2026, the released OTel models had been downloaded over 16 million times, and the Open Telco AI project had received 157+ pieces of media coverage worldwide. sentence-transformers/all-MiniLM-L12-v2 -> OTel-Embedding full-parameter post-training -> att/OTel-Embedding-34M Standard errors are computed with bootstrap resampling (n=1000) over the held-out OTel evaluation partition. NDCG@10 measures whether relevant telecom passages are ranked near the top of the retrieved list. The model was trained on telecom-focused data curated by 100+ domain experts. The raw corpus contained roughly 1.1M training points and was filtered to 326,767 higher-confidence examples. Released datasets: OTel-LLM, OTel-Embedding,…
Read the full model card ↗ · Preview checked 2026-11-01T15:39:14.250Z
Inside the original model card — Document outline
- OTel-Embedding-34M
- Community Use
- Model Details
- Model Lineage
- OTel vs. Base Model
- Evaluation Caveats
- Training Data
- Representative Training Row
- Intended Use
- Training Recipe
- Usage
- Limitations and Responsible Use
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Model overview
att/OTel-Embedding-34M is a feature-extraction model repository published by att on Hugging Face. A library was not reported.
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Model facts
- Task
- feature-extraction
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 33,360,000
- Architecture
- BertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-23T06:14:42.000Z
- Last modified
- 2026-10-23T06:14:47.000Z
Compatibility and lineage
Reported languages: en
Reported base models: sentence-transformers/all-MiniLM-L12-v2
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-23T06:46:00.441Z. Daily imports are snapshots, not real-time monitoring.
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