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- LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
In this work, we introduce LLM2Vec, a simple unsupervised approach that can transform any decoder-only LLM into a strong text encoder LLM2Vec consists of three simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning
- llm2vec · PyPI
LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning
- LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders - GitHub
LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning
- LLM2Vec: Large Language Models Are Secretly Powerful Text En
Did you know that our most advanced language models might be hiding a secret talent? Scientists have just unveiled a new technique called LLM2Vec that transforms these models into powerful text encoders This means they can understand and represent text in ways we never thought possible!
- LLM2Vec Large Language Models - ServiceNow Blog
We’re excited to present LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders, a simple and efficient solution to transform any decoder-only LLM into a powerful text encoder in an unsupervised fashion simply by using adapters (LoRA), without the need to modify the base models
- McGill-NLP LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised - Hugging Face
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
- LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders . . .
LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders It consists of 3 simple steps: 1) enabling bidirectional attention, 2) training with masked next token prediction, and 3) unsupervised contrastive learning
- Large language model - Wikipedia
A large language model (LLM) is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation [1][2] The largest and most capable LLMs are generative pre-trained transformers (GPTs) and provide the core capabilities of modern chatbots
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