The demand for tools to simplify and optimize Generative AI development is increasing rapidly. New tools like NVIDIA AI Workbench are making it easier than ever for developers to tune AI models to their specific needs. NVIDIA AI Workbench, part of the RTX AI Toolkit, allows users to develop and experiment with AI applications on various GPU systems, from laptops to data centers. It simplifies technical tasks and collaboration, making it easier for both experts and beginners.
NVIDIA AI Workbench addresses challenges in AI project development by streamlining the setup process, integration with version control and project management tools, and ensuring consistency when scaling from on-premises to the cloud. The tool also offers sample projects, such as the Hybrid RAG Workbench Project, which allows users to run custom text-based RAG web applications locally or remotely. This project supports a wide variety of large language models and allows users to run inference wherever they choose.
In addition to the Hybrid RAG project, developers can use the Flame Factory AI Workbench Project for fine-tuning AI models for specific use cases. This project enables QLoRa fine-tuning and model quantization through a simple graphical user interface. Once tuning is complete, the model can be quantized for improved performance and memory efficiency.
The AI Workbench projects can be run on a user’s preferred system without the need for complex infrastructure setup. This flexibility extends to all Workbench projects, allowing users to adjust and customize as needed. By subscribing to the AI Newsletter Decoded, developers can stay up-to-date on the latest advancements in Generative AI for gaming, video conferencing, and interactive experiences.
Article Source
https://blogs.nvidia.com/blog/ai-decoded-workbench-hybrid-rag/
