NeuML/pubmedbert-base-embeddings
sentence-similarity model by NeuML
From the publisher
Model card & documentation
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This is a PubMedBERT-base model fined-tuned using sentence-transformers. It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. The training dataset was generated using a random sample of PubMed title-abstract pairs along with similar title pairs. PubMedBERT Embeddings produces higher quality embeddings than generalized models for medical literature. Further fine-tuning for a medical subdomain will result in even better performance. This model can be used to build embeddings databases with txtai for semantic search and/or as a knowledge source for retrieval augmented generation (RAG). Alternatively, the model can be loaded with sentence-transformers. The model can also be used directly with Transformers. Performance of this model compared to the top base models on…
Read the full model card ↗ · Preview checked 2026-10-30T18:54:07.814Z
Inside the original model card — Document outline
- PubMedBERT Embeddings
- Usage (txtai)
- Usage (Sentence-Transformers)
- Usage (Hugging Face Transformers)
- Evaluation Results
- Training
- Full Model Architecture
- More Information
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
NeuML/pubmedbert-base-embeddings is a sentence-similarity model repository published by NeuML on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 1,058,035
- Cumulative likes
- 207
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 109,482,240
- Architecture
- BertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2023-10-18T14:22:18.000Z
- Last modified
- 2026-04-21T12:44:28.000Z
Compatibility and lineage
Reported languages: en
Reported base models: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
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.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:31.802Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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