Predibase

Predibase is the fastest, most efficient way to fine-tune and serve open-source #LLMs. 🔥 As the first platform designed to help #engineers productionize open-source AI, Predibase makes it easy to customize LLMs on scalable managed infra in your cloud—at a fraction of the cost of commercial LLMs. Don't believe us? Try it out for free! Fine-tune and serve Llama-2 with our two week free trial: https://pbase.ai/3SnGq2z

Big models, who? #SLMs are in! 😎 What's driving the rise of small language models and why are companies like Apple all in? Check out Devvret Rishi's recent article in Solutions Review for a deep dive on how these little models punch above their weight class, enabling organizations to build smaller, faster, more efficient #GenAI applications. https://lnkd.in/gNjReTBP

🔥 NEW Tutorial + Notebook: Beat #GPT4o with only 10 Rows of Data 🔥 Lack of training data is the #1 blocker to fine-tuning a high-quality #SLM. Not anymore! Check out our latest deep dive tutorial to learn how to generate effective #synthetic datasets with only 10 sample data points and use that data to fine-tune a high-precision SLM that outperforms #GPT4o. What's inside: 🛠 Comparison of different synthetic generation techniques 💡 How to enhance data generation with a mixture of agents (#MoA) pipeline 🧠 How to easily and efficiently fine-tune Llama-3.1-8b 📊 #Benchmarks comparing fine-tuned SLMs vs. GPT4o ✅ Best practices when generating your own #syntheticdata Happy fine-tuning! Tutorial link: https://lnkd.in/g6euVaVk And, thank you Chloe Leung for creating this awesome tutorial!

🔥 Where can you see the latest innovations in #GenAI tech? At The GenAI Collective Demo Day in #SF on Dec 4th!🔥 10 startups will showcase cutting edge applications for #LLMs. Don't miss it and save your spot - it fills up fast: https://lu.ma/demo-night. We're excited to cohost this event with the The GenAI Collective, Product Hunt, SHACK15 Ventures and Graphite!

🔥 Where can you see the latest innovations in #GenAI tech? At The GenAI Collective Demo Day in #SF on Dec 4th!🔥 10 startups will showcase cutting edge applications for #LLMs. Don't miss it and save your spot - it fills up fast: https://lu.ma/demo-night. We're excited to cohost this event with the The GenAI Collective, Product Hunt, SHACK15 Ventures and Graphite!

Turbo #LoRA just got even better! If you’ve already trained a LoRA, there’s no need to start from scratch. You can now keep your original LoRA weights intact and add the Turbo speculator in a quick, seamless process – resulting in a 2x+ #throughput boost without sacrificing model quality. With our task-specific speculative decoding, we’re seeing up to 365 #tokens per second on top-tier hardware—setting a new benchmark in performance! 📈 Stay tuned as we roll out these enhancements to make your models faster and more efficient than ever. Catch the full webinar replay: https://lnkd.in/geTyXrVH

🌉 Bay Area Friends: Are you headed to the Open Data Science Conference (ODSC) tomorrow in Burlingame? Don't miss this talk from ML Eng Lead Arnav Garg to learn how to easily customize your own #SLMs and put into production for #GenAI applications at scale! Talk details: https://lnkd.in/g93-fZFh ➡ And if you can't make the conference, check out this replay from our recent webinar on all things #inference optimization: https://lnkd.in/geTyXrVH

⚡ Missed Our Webinar? Let’s Talk GPU Autoscaling for Fine-Tuned SLMs! Scaling AI workloads efficiently is hard—but it doesn’t have to be. In our webinar, we cover how efficient GPU autoscaling can help you: 🔄 Handle unpredictable traffic surges without manual intervention 💸 Optimize costs by scaling GPUs only when needed 📈 Hit your throughput SLAs even during peak demand 🌍 Maintain reliability with multi-region load balancing and auto-failover Want to learn more? Check out the replay: https://pbase.ai/48sLSXY

Top 3 challenges ML engineers face putting #SLMs into production: 1️⃣ Performance Bottlenecks: poor #latency = slow response times = bad customer experiences. 2️⃣ Engineering Complexity: building and managing scalable and reliable serving #infra for open-source SLMs is resource-intensive and requires deep LLMOps expertise. 3️⃣ High Infra Costs: always-on deployments that don't #autoscale up/down blow through budgets as use cases and traffic grows. How do you overcome these challenges? 🤔 Check out this article in Marktechpost Media Inc. for our playbook: https://lnkd.in/gdpGkGmQ

Fine-tuning #SLMs is the easy part. Putting them into #production and hitting SLAs is much more complex. Joins us to learn how to optimize inference for your fine-tuned models: 💣 💥 Landmines to avoid when producitionizing SLMs 🚀 How to 4x #throughput with Turbo LoRA, Spec Decoding and FP8 🔄 What it takes to build #reliable infra w/ multi-region load balancing and auto-failovers 🚦 How to scale for production traffic with #autoscaling GPUs Save your spot: https://lnkd.in/gMkcAmfX