Uploaded January 2026 | Updated September 2026, 2 weeks ago

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In part 7, we walk through a full hands-on workflow for generating embeddings externally and importing them into Weaviate using the Bring Your Own Vectors approach.

In this section, we're going to go over:
- Generating embeddings using a Hugging Face model (ModernBERT) in Google Colab
- Sampling and preparing a large dataset for embedding generation
- Converting text (titles + abstracts) into vector embeddings using Sentence Transformers
- Setting up a free Weaviate Cloud sandbox cluster
- Connecting Colab to Weaviate using API keys and cluster endpoints
- Creating a custom collection with vectorizer disabled for external embeddings
- Inserting embeddings, metadata, and text into Weaviate at scale

This workflow shows how easy it is to bring your own vectors into Weaviate and manage your embeddings end-to-end—giving you full control over vector generation, storage, and retrieval.

#EmbeddingGeneration #Weaviate #APIIntegration #SentenceTransformers #GoogleColab
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