LangChain and LlamaIndex streamline ChatGPT and LLM application development. Boost your project’s efficiency with LangChain’s tools and modules, and LlamaIndex’s advanced document handling. Discover the future of language model orchestration today.
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Interos, a leading supply chain management company, partnered with Winder.AI to enhance their machine learning operations (MLOps). Together, we developed advanced MLOps technologies, including a scalable annotation system, a model deployment suite, AI templates, and a monitoring suite. This collaboration, facilitated by open-source software and Kubernetes deployments, significantly improved Interos’ AI maturity and operational efficiency.
Read moreThe article explores the complexities and nuances of monitoring and evaluating Large Language Models (LLMs) like ChatGPT in business applications. It emphasizes the insufficiency of traditional metrics, the importance of real-time tracking, human feedback, and specialized evaluation methods to ensure model safety, efficiency, and performance optimization.
Read moreThis notebook demonstrates how to fine-tune a state-of-the-art large language model (LLM) on a single GPU. This example uses Falcon-7B because it is Apache licensed. The data used in this notebook is for informational purposes only, do not use this data unless you have licensed it.
Read moreIn our previous articles, you learned how to build and train your personal ChatGPT model (large-language model). However, it’s important to understand that these models are merely components within a larger software landscape. After achieving adequate performance in a controlled environment, the next step is to integrate it into your broader system.
Read moreWe’re pleased to announce the release of Stable Audio, a new generative AI music service. Stable Audio is a collaboration between Stability AI and Winder.AI that leverages state-of-the-art audio diffusion models to generate high-quality music from a text prompt.
Read moreIn just a few years since the transformer architecture was first published, large language models (LLMs) have made huge strides in terms of performance, cost, and potential. In the previous two parts of this series, we’ve already explored the fundamental principles of such models and the intricacies of the development process.
Yet, before an AI product can reach its users, the developer must make yet more key decisions. Here, we’re going to dig into whether you should train your own ChatGPT model with custom data.
Read moreThis is a video of a workshop about deep reinforcement learning (DRL). First presented at ODSC London in 2023, it is nearly three hours long and covers a wide variety of topics. Split into three sections, the video introduces DRL and RL applications, explains how to develop an RL project, and walks you through two RL example notebooks.
Read moreThe premise of LLMs is beautifully exemplified by products like ChatGPT, that use these models to power conversational interfaces, offering a seamless and engaging chat user experience. In this second part of our series on ChatGPT, we provide an overview of what it’s like to develop against commercial LLM offerings and what it takes to begin developing your bespoke model.
Read moreThis guide explores developing Auth0 applications on Cloudflare Pages, focusing on the transition from Node.JS to the V8 runtime and its impact on JavaScript frameworks like Next.JS.
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