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Getting started with retrieval augmented generation on BigQuery with LangChain

The ability of large language models (LLMs) to process and generate human language continues to revolutionize many aspects of business. But an LLM’s knowledge is limited to the data it was trained on, which can cause drawbacks when dealing with specific company information or nuanced industry contexts. Retrieval-augmented generation (RAG) offers a powerful solution to …

CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement

Contrastive language image pretraining (CLIP) is a standard method for training vision-language models. While CLIP is scalable, promptable, and robust to distribution shifts on image classification tasks, it lacks object localization capabilities. This paper studies the following question: Can we augment CLIP training with task-specific vision models from model zoos to improve its visual representations? …