Inferless

🚀 Why GGUF Stands Out for LLM Quantization? If you’re exploring quantization options for large language models, GGUF deserves a look. Here’s why it stands apart: • Precision: GGUF maintains accuracy even in lower-bit formats. • Compatibility: Smoothly integrates with all LLMs, unlike many other formats. • Efficiency: GGUF strikes a balance between model size and speed. For devs optimizing LLMs, GGUF is a win. Read more here: https://dub.sh/ingguf

🚀 Easily Deploy Whisper Large V3 Turbo with Inferless! Get high-quality speech-to-text up fast—just sign up, set your API key, and deploy. Link to repo here: https://dub.sh/wlv3turboin

Unlock Peak LLM Performance with GGUF Optimizations 🚀 We just released the ultimate guide for boosting LLMs performance using GGUF optimizations. Whether you're looking to reduce inference time, optimize memory usage, or scale more efficiently—this guide has everything you need. 🔑 Key Takeaways: • How GGUF improves model loading & runtime • Practical steps to integrate GGUF in your LLM workflows • Real-world performance improvements (with data!) 💡 Check out the full article here: https://dub.sh/ingguf

2 days left for our live townhall on Inferless Usecases RSVP today: https://dub.sh/townhalloct

5 days left for our live townhall on Inferless Usecases RSVP today: https://dub.sh/townhalloct

Join us for our October Live Townhall to learn about popular use-cases for Inferless from spiky workloads, dynamic batching and more Oct 23rd | 9 AM PT — Don't miss it! RSVP here :https://dub.sh/townhalloct

🚀 Improved Docker Build Logs Are Here! No more waiting till the end to see what’s happening. Build logs now stream in real-time, giving you instant visibility into your custom runtime builds. Track progress faster. Troubleshoot easier. Get back to building. 🔧

Calling all ML devs in SF 👀 Join our next breakfast on October 17th, ▶︎ For devs and founders ▶︎ Discuss real-world AI deployment ▶︎ Casual, no pitches Limited slots. RSVP. https://lnkd.in/gRnscsfU

Join us as we explore the differences between URLs, URNs, and URIs, and why they often confuse developers. We’ll also dive into the limitations of using build pipelines for test automation, the potential of self-healing electronic skin, and the challenges of deploying machine learning models on Kubernetes with Nilesh Agarwal (Co-Founder & CTO, Inferless) and James Card (Chief Engineer, Skymond). Episode 24 is now live! 🔴

🚀 Check out this quick video on how to deploy the latest Llama-3.2-11B-Vision-Instruct using Inferless! For a detailed step-by-step guide: https://dub.sh/llama3.2in Request access here: https://dub.sh/in-request