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www.mixedbread.ai | ||
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saeedesmaili.com
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| | | | | Recently, I've been working on a side project where I use OpenAI's text-embedding-ada-002 model to generate vector embeddings for text snippets. While this model is inexpensive, the cost can add up when dealing with thousands or millions of text snippets. Therefore, I decided to explore alternatives, particularly those that would allow me to run similar models locally instead of relying on OpenAI's API. In this post, I'll share my experience using the sentence-transformers library for this purpose and discuss the pros and cons. | |
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www.nomic.ai
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| | | | | Nomic expands the capabilities of Nomic Embed to include vision. | |
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blog.nomic.ai
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| | | | | Nomic releases a 8192 Sequence Length Text Embedder that outperforms OpenAI text-embedding-ada-002 and text-embedding-v3-small. | |
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bdtechtalks.com
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| | | Retrieval augmented generation (RAG) enables you to use custom documents with LLMs to improve their precision. | ||
