节点与集成
Embeddings HuggingFace Inference
Use the Embeddings HuggingFace Inference node to generate embeddings1 for a given text.
On this page, you'll find the node parameters for the Embeddings HuggingFace Inference, and links to more resources.
Node parameters
- Model: Select the model to use to generate the embedding.
Refer to the Hugging Face models documentation for available models.
Node options
- Custom Inference Endpoint: Enter the URL of your deployed model, hosted by HuggingFace. If you set this, n8n ignores the Model Name.
Refer to HuggingFace's guide to inference for more information.
Templates and examples
Browse Embeddings HuggingFace Inference node documentation integration templates or search all templates
Related resources
Refer to Langchain's HuggingFace Inference 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
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