The release of WordLlama on Hugging Face marks a pivotal moment in natural language processing (NLP). This advanced language model is designed to offer developers, researchers, and businesses a highly efficient and accessible tool for various NLP applications.
An article discussing a paper that proposes a new framework, MetRag, for retrieval augmented generation. The framework is designed to improve the performance of large language models in knowledge-intensive tasks.
This article explains how to use the Sentence Transformers library to finetune and train embedding models for a variety of applications, such as retrieval augmented generation, semantic search, and semantic textual similarity. It covers the training components, dataset format, loss function, training arguments, evaluators, and trainer.
A surprising experiment to show that the devil is in the details
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Object Similarity Search
Robust OCR Document Search
Semantic Search
Cross-modal Retrieval
Probing Perceptual Similarity
Comparing Model Representations
Concept Interpolation
Concept Space Traversal
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