LLMWare Introduces Model Depot: An Extensive Collection of Small Language Models (SLMs) for Intel PCs

LLMWare.ai Launches Model Depot for Intel PCs **What is Model Depot?** LLMWare.ai has launched Model Depot on Hugging Face, offering over 100 Small Language Models (SLMs) designed for Intel PCs. This resource is useful for various tasks like chatting, coding, and math, making it a great asset for the open-source AI community. **Practical Solutions for Developers** Model Depot, along with LLMWare’s open-source library, helps developers create advanced AI workflows easily. This includes features like Retrieval Augmented Generation (RAG) and agent-based workflows specifically for Intel hardware. The OpenVINO library boosts the performance of deep learning models, making them suitable for many devices. **Benefits of OpenVINO and ONNX** OpenVINO enhances model performance on Intel devices, while ONNX ensures that models work across different AI frameworks. This flexibility allows developers to select the best tools for their hardware, improving application efficiency. **Performance Insights** Recent tests show that using 4-bit quantized SLMs with OpenVINO can greatly improve performance. For example, a Dell laptop with an Intel Core Ultra 9 achieved inference speeds up to 7.6 times faster than traditional methods. **Access to Optimized Models** Model Depot gives developers access to popular SLMs like Microsoft Phi-3 and Llama. This helps them build efficient workflows that maximize AI capabilities on Intel PCs, allowing businesses to deploy AI applications securely and cost-effectively. **Collaboration with Intel** LLMWare has teamed up with Intel to create Model HQ, a no-code solution for developing AI applications. This platform is user-friendly and includes strong security features, making it easy for businesses to create and launch AI applications. **Empowering Enterprises with AI** LLMWare aims to make AI deployment simpler for businesses, focusing on local and secure solutions. By providing high-quality models and tools, they help companies effectively use AI and remain competitive. **Get Involved** Check out LLMWare’s resources on GitHub and Hugging Face, and visit llmware.ai for the latest updates. For AI management advice, contact hello@itinai.com, and follow us on Telegram and Twitter for ongoing information.