text: Jina | ğŸ¦œï¸�ğŸ”— Langchain
  
  
  
  
  
  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 modelsJinaJinaLet's load the Jina Embedding class.from langchain.embeddings import JinaEmbeddingsembeddings = JinaEmbeddings(    jina_auth_token=jina_auth_token, model_name="ViT-B-32::openai")text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])In the above example, ViT-B-32::openai, OpenAI's pretrained ViT-B-32 model is used. For a full list of models, see here.PreviousInstructEmbeddingsNextLlama-cppCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.