Sentence Transformers in the Hugging Face Hub
Over the past few weeks, we've built collaborations with many Open Source frameworks in the machine learning ecosystem. One that gets us particularly excited is Sentence Transformers.
Sentence Transformers is a framework for sentence, paragraph and image embeddings. This allows to derive semantically meaningful embeddings (1) which is useful for applications such as semantic search or multi-lingual zero shot classification. As part of Sentence Transformers v2 release, there are a lot of cool new features:
Sharing your models in the Hub easily.
Widgets and Inference API for sentence embeddings and sentence similarity.
Better sentence-embeddings models available (benchmark and models in the Hub).
Over the past few weeks, we've built collaborations with many Open Source frameworks in the machine learning ecosystem. One that gets us particularly excited is Sentence Transformers.
Sentence Transformers is a framework for sentence, paragraph and image embeddings. This allows to derive semantically meaningful embeddings (1) which is useful for applications such as semantic search or multi-lingual zero shot classification. As part of Sentence Transformers v2 release, there are a lot of cool new features:
Sharing your models in the Hub easily.
Widgets and Inference API for sentence embeddings and sentence similarity.
Better sentence-embeddings models available (benchmark and models in the Hub).