With great enthusiasm, we unveil the Prem-1B series, an open-source, multipurpose large language model developed by Prem AI. This cutting-edge SLM offers the open community and enterprises the opportunity to harness capabilities that were once exclusively available through closed-model APIs, empowering them to build their advanced language models. The weights
Last week, we open-sourced PremSQL, a local first library that created customized Text-to-SQL solutions. When deploying RAG-based services (whether on documents or databases) for enterprises, it becomes crucial that the underlined data is not exposed to third-party APIs. With PremSQL, you can use our ready-made pipelines or customize and create
So you are given some Python project which creates an API endpoint which does some AI/ML inference. You need to run this on your own infra, a cloud VM or whatever. What do you do?
Function calling is seen as revolutionary in chatbots, enhancing real-time capabilities. However, older NLU + Core bots handled many use cases effectively. This article explores the evolution of chatbots, weighing the hype of function calling against the proven efficiency of traditional methods.
The era of GPT-4's dominance is ending as diverse, specialized language models take the stage. Companies now favor both open-source and proprietary models tailored to specific tasks, moving away from one-size-fits-all solutions. Small Language Models (SLMs) offer efficiency for niche needs.
PremSQL is a local-first, open-source Text-to-SQL solution that ensures data privacy and control by avoiding third-party models. With support for small language models, PremSQL simplifies natural language querying and provides autonomous, AI-driven data analysis.
Explore the latest Text-to-SQL advancements in our new blog. We evaluate top models like GPT-4o and Llama using the newly released text2sql package on BIRDBench. Learn about Execution Accuracy, Valid Efficiency Score, and how open-source models are challenging closed-source alternatives.
Text to SQL is a task that aims to convert natural language questions into corresponding SQL queries that can be executed in relational databases. Interestingly, this problem statement has been through research before the rise of Large Language Models.
At Prem, we believe that the future of AI is Sovereign. This is why we are building a comprehensive ecosystem to enable companies worldwide to fully benefit from the potential of generative AI while retaining ownership and control of their data. Today, I am excited to share that we have
Today, we are excited to announce the open-source release of the “Prem-Operator,” A Kubernetes operator that eases the deployment of AI and ML workloads, with an initial focus on inference. The launch of the Prem Operator marks a major advancement in our goal to provide AI that you can fully
We believe in giving back to the community. So today we introduce Prem Benchmarks. This is a fully open-source project with its primary objective being to benchmark popular LLM inference engines (currently 13 + engines) like vLLM, TensorRT LLM, HuggingFace Transformers, etc on different precisions like float32, float16, int4, and int8.
Imagine a student taking a closed-book exam, relying solely on what they've memorized. This is how traditional large language models (LLMs) operate, using only the data they were trained on. Retrieval-augmented generation (RAG) changes this by allowing the model, like a student now taking an open-book exam, to