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Sentence Transformers Embeddings Configuration

Sentence Transformer Embeddings Configuration Interface The Sentence Transformers configuration screen in PipesHub where you’ll enter your Model Name PipesHub allows you to use Sentence Transformer embedding models to enable semantic search and document retrieval in your workspace. These models run locally inside PipesHub — no external API, no API key, and no usage costs.

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Required Fields

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Model Name *

The Model Name is the only required field. It defines which Sentence Transformer model you want to use. Popular Sentence Transformer models include:
  • all-MiniLM-L6-v2 - Lightweight general-purpose model, good balance of speed and quality
  • all-mpnet-base-v2 - Higher accuracy general-purpose model
  • paraphrase-multilingual-mpnet-base-v2 - Supports 50+ languages for multilingual applications
How to choose a model:
  • For general purpose use, select all-MiniLM-L6-v2
  • For higher accuracy when speed is less critical, select all-mpnet-base-v2
  • For multilingual content, select paraphrase-multilingual-mpnet-base-v2
  • Check the Sentence Transformers documentation for the full list of available models

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Configuration Steps

As shown in the image above:
  1. Click Configure on the Sentence Transformers provider card
  2. Specify your desired Model Name (marked with *)
  3. Click Add Model to save and validate
Model Name is the only required field. No API key or external service is needed — the model runs locally inside PipesHub.

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Usage Considerations

  • No external API calls are made — all embedding happens locally inside PipesHub
  • No API key or billing setup required
  • Larger models provide better quality but require more memory and are slower to load
  • Most models support a maximum sequence length of 128–512 tokens per document chunk

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Troubleshooting

  • If you encounter errors, verify the model name is spelled correctly
  • For memory issues, consider switching to a smaller model such as all-MiniLM-L6-v2
  • For multilingual applications, ensure you are using a model that supports your target languages
For additional support, refer to the Sentence Transformers documentation or contact PipesHub support.