ellamind
/

e5small_sgb_aktg_bmf_experimental

Sentence Similarity

sentence-transformers

feature-extraction

text-embeddings-inference

Inference Endpoints

🇪🇺 Region: EU

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jphme commited on 16 days ago

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 e5 Small trained on the SGB5, AktG + train set of the BMF-Rundschreiben (19k queries in total).
-This mdoel is the `e5small_tuned3_val_bmf` version.
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/647ef81ce9c81260ff84fdd7/8hVkoYUQuIB4ZFjC_dnz5.png)
-**Disclaimer: Please note that this model is named sgb_aktg_bmf due to (public) SGB, AKTG and BMF-Rundschreiben data, which was used to train it. It has no connection to any public entity and was built internally by ellamind.**
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.

 e5 Small trained on the SGB5, AktG + train set of the BMF-Rundschreiben (19k queries in total).
+**Disclaimer: Please note that this model is named sgb_aktg_bmf due to (public) SGB, AKTG and BMF-Rundschreiben data, which was used to train it. It has no connection to any public entity and was built internally by ellamind.**
+This model is the `e5small_tuned3_val_bmf` version in the image below:
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/647ef81ce9c81260ff84fdd7/8hVkoYUQuIB4ZFjC_dnz5.png)
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.