This post is divided into two parts; they are: • Contextual Keyword Extraction • Contextual Text Summarization Contextual keyword extraction is a technique for identifying the most important words in a document based on their contextual relevance. Source link
Quantization might sound like a topic reserved for hardware engineers or AI researchers in lab coats. Source link
Machine learning models are trained on historical data and deployed in real-world environments. Source link
LLMs show impressive capabilities across numerous applications, yet they face challenges due to computational demands and memory requirements. This challenge is acute in scenarios requiring local deployment for privacy concerns, such as processing sensitive patient records, or compute-constrained environments like…
Using llama. Source link
In this notebook, we demonstrate how to build a fully in-memory “sensor alert” pipeline in Google Colab using FastStream, a high-performance, Python-native stream processing framework, and its integration with RabbitMQ. By leveraging faststream.rabbit’s RabbitBroker and TestRabbitBroker, we simulate a message…
