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www.mixedbread.ai | ||
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unstructured.io
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| | | | | Navigate the Massive Text Embedding Benchmark (MTEB) leaderboard with confidence! Understand the difference between Bi-Encoders and Cross-Encoders, learn how text embedding models are pre-trained and benchmarked, and how to make the best choice for your specific use case. | |
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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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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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haifengl.wordpress.com
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| | | Generative artificial intelligence (GenAI), especially ChatGPT, captures everyone's attention. The transformerbased large language models (LLMs), trained on a vast quantity of unlabeled data at scale, demonstrate the ability to generalize to many different tasks. To understand why LLMs are so powerful, we will deep dive into how they work in this post. LLM Evolutionary Tree... | ||
