text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsSentence Transformers EmbeddingsSentence Transformers EmbeddingsSentenceTransformers embeddings are called using the HuggingFaceEmbeddings integration. We have also added an alias for SentenceTransformerEmbeddings for users who are more familiar with directly using that package.SentenceTransformers is a python package that can generate text and image embeddings, originating from Sentence-BERTpip install sentence_transformers > /dev/null        [notice] A new release of pip is available: 23.0.1 -> 23.1.1    [notice] To update, run: pip install --upgrade pipfrom langchain.embeddings import HuggingFaceEmbeddings, SentenceTransformerEmbeddingsembeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")# Equivalent to SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text, "This is not a test document."])PreviousSelf Hosted EmbeddingsNextSpacy