节点与集成
Embeddings Ollama
Use the Embeddings Ollama node to generate embeddings1 for a given text.
On this page, you'll find the node parameters for the Embeddings Ollama node, and links to more resources.
Node parameters
- Model: Select the model to use to generate the embedding. Choose from:
- all-minilm (384 Dimensions)
- nomic-embed-text (768 Dimensions)
Learn more about available models in Ollama's models documentation.
Templates and examples
Browse Embeddings Ollama node documentation integration templates or search all templates
Related resources
Refer to Langchain's Ollama embeddings documentation for more information about the service.
View n8n's Advanced AI documentation.
Footnotes
- Back
Embeddings are numerical representations of data using vectors. They're used by AI to interpret complex data and relationships by mapping values across many dimensions. Vector databases, or vector stores, are databases designed to store and access embeddings.
官方原文和授权
本页来自 N8N 英文官方网站固定快照，并转换成 xueai 静态页面。内容以 N8N 持续更新的官方页面为准。