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  > LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.
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  - **Repository:** https://github.com/McGill-NLP/llm2vec
 
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  ## Installation
 
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  > LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.
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  - **Repository:** https://github.com/McGill-NLP/llm2vec
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+ - **Paper:** https://arxiv.org/abs/2404.05961
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  ## Installation