sentence-transformers-alephbert

Model overview

sentence-transformers-alephbert is published by imvladikon as a sentence-similarity model. The captured configuration identifies BertModel with model type bert and the sentence-transformers library. According to the model card, the current version is a distillation of the LaBSE model on a private corpus, mapping sentences and paragraphs to 768-dimensional dense vectors.

Recorded capabilities

Use cases in the source record

• Hebrew semantic search and clustering over sentence and paragraph embeddings, as described in the model card with Hebrew example sentences.
• Sentence-embedding retrieval with mean pooling, usable through sentence-transformers or directly through Transformers per the documented workflows.

Limitations and unknowns

• No parameter count was extracted from this record.
• No license value was extracted from this record.
• The distillation corpus is described only as a private corpus, with no further detail extracted.
• No evaluation results were extracted from this record.
• Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: imvladikon/sentence-transformers-alephbert

Captured: Unknown. Processed: 2026-09-07T19:34:47.113985+00:00.

imvladikon/sentence-transformers-alephbert[WIP] This is a sentence-transformers model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. Current version is distillation of the LaBSE model on private corpus. Usage (Sentence-Transformers) Using this model becomes easy when you have sentence-transformers installed: pip install -U sentence-transformers Then you can use the model like this: from sentence_transformers import SentenceTransformer from sentence_transformers.util import cos_sim sentences = [ "הם היו שמחים לראות את האירוע שהתקיים." , "לראות את ה…