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Introduction In today’s information-driven world, delivering precise and contextually relevant search results is a critical challenge. This is where RAG (Retrieval-Augmented Generation) systems shine, combining the power of retrieval-based approaches with advanced generation models to enhance search accuracy and relevance. In this blog, we’ll explore how to build a robust RAG-based search system using a […]
Have you ever performed with AI chatbots like ChatGPT or Claude? They’re first-rate equipment that can help us write, clear up issues, and create content. But just like any generation, they can be susceptible to certain hints or manipulations. One such vulnerability is referred to as a “prompt assault.” Let’s smash down what this means […]
Introduction Fine-tuning large language models for code generation typically requires significant computing power. Many popular models, such as Code LLaMA or CodeT5, demand high-performance GPUs like NVIDIA A100, making them less accessible for most users. However, by leveraging LoRA (Low-Rank Adaptation) and quantization techniques with libraries such as `BitsAndNytes` and `PEFT`, you can fine-tune Starcoder2 […]
Introduction The financial industry generates vast amounts of complex data, from annual reports to contractual obligations, which often need to be analyzed for strategic decision-making. Manually processing and extracting insights from these documents is time-consuming and prone to error. Agentic GraphRAG, is a cutting-edge technology that leverages graph-based retrieval and generative models to revolutionize how […]