Abhishek Choudhary’s Post

New feature alert 🚀 Tensorfuse now supports working with Github Actions! With our latest update, you can: 1. Automate your CI/CD that runs on GPUs 2. Have full control with customisable parameters like types of GPUs, scaling parameters, and secrets. Watch the video to see how Tensorfuse and GitHub Actions can supercharge your deployment workflows!

GigaIO's memory fabric, powered by #FabreX software, breaks the limits of server chassis by enabling seamless server-to-server and device-to-device communication. Compose and scale resources like GPUs, FPGAs, and NVMe dynamically across multiple servers using native #PCIeprotocols. With Redfish® API integration, automate and orchestrate with ease. Unlock new possibilities for your workloads today: https://bit.ly/477qcA3

We’re excited to expand the functionality of Snowflake ML with the new Container Runtime for Snowflake Notebooks, available in public preview! Container Runtime provides flexible infrastructure for building and running resource-intensive ML workflows within Snowflake. Using Snowflake Notebooks in Container Runtime gives you access to distributed processing on both CPUs and GPUs, optimized data loading, automatic lineage capture, and Model Registry integration. It also provides flexibility to leverage a set of preinstalled packages or the ability to pip install any open-source package of choice. Our Quickstart will guide you through installing packages, training a model, and viewing logs. Try it out: https://lnkd.in/gdwSmXV8

Can you build a machine to run the FULL Deepseek R1 locally? No WAY right? Well, yeah someone did! 🤯 Even more amazingly, with NO GPUs… Someone designed a local server that can serve the FULL Deepseek-R1 for $6000. It's not fast (6-8 tokens per second or c.4-5 words a second) but it's interesting because: - no GPUs at all (adding them would push the price up to closer to $100k) - with no GPUs power consumption is decent (400W, typical workstation) - outRAGEous amounts of memory needed (768GB) - the R1 model file is 700GB. I'm stuck behind some aged copper internet here in London and can only get 8-10MB/s which … sucks…

🎉 Thrilled to share that Container Runtime for Snowflake Notebooks is now in public preview! Snowflake is making it easier than ever before to build and deploy models while using distributed GPUs, all from a single platform. ❄️ Check out the blog to learn more - as always, link in the first comment 🔗

🚀 2025: The Year of Smarter Workflows The rise of Arm CPUs is reshaping the way we think about delivering low-cost inference models across a host of applications. As these powerful, efficient processors become more integral, they offer a unique opportunity to optimize for cost and performance. But hardware alone isn’t enough — success comes from seamlessly integrating this technology into your core workflows. That’s where GitHub Actions shines. Automate, iterate, and scale your Arm-based workloads with the same tools your team already loves. From CI/CD pipelines to infrastructure automation, GitHub Actions helps you stay ahead in 2025. 💡 Ready to future-proof your workflows? Let’s build it together. #ArmCPU #InferenceModels #GitHubActions #Automation #FutureOfWork https://lnkd.in/eD2EHUXs

This post examines how different software components came together to allow LLM-as-judge evaluation without the need for expensive GPUs. All the components were built with and chosen for their user control, open source nature, and interoperability. https://lnkd.in/ePhve9n3

It's been a crazy year! For our last release of 2024, we shipped: ⚒️ 𝐌𝐮𝐥𝐭𝐢-𝐆𝐏𝐔 𝐖𝐨𝐫𝐤𝐞𝐫𝐬 You can now run workloads across multiple GPUs! This lets you run workloads that might not fit on a single GPU. For example, you could run a 13B parameter LLM on 2x A10Gs, which normally would only fit on a single A100-40. ⚡️𝐈𝐧𝐬𝐭𝐚𝐧𝐭𝐥𝐲 𝐖𝐚𝐫𝐦 𝐔𝐩 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫𝐬 We added a "Run Now" button to the dashboard to instantly invoke an app and warm up the container. 🚢 𝐈𝐦𝐩𝐨𝐫𝐭 𝐋𝐨𝐜𝐚𝐥 𝐃𝐨𝐜𝐤𝐞𝐫𝐟𝐢𝐥𝐞𝐬 We wanted to make it easier to use existing Docker images on Beam. You can now use a Dockerfile that you have locally to create your Beam image. 🔑 𝐏𝐚𝐬𝐬 𝐒𝐞𝐜𝐫𝐞𝐭𝐬 𝐭𝐨 𝐈𝐦𝐚𝐠𝐞 𝐁𝐮𝐢𝐥𝐝𝐬 You can now pass secrets into your image builds, useful for accessing private repos or running build steps that require credentials of some kind. 𝐀𝐧𝐝 𝐰𝐞'𝐯𝐞 𝐠𝐨𝐭 𝐬𝐨𝐦𝐞 𝐚𝐦𝐚𝐳𝐢𝐧𝐠 𝐧𝐞𝐰 𝐟𝐞𝐚𝐭𝐮𝐫𝐞𝐬 𝐜𝐨𝐦𝐢𝐧𝐠 𝐢𝐧 𝐉𝐚𝐧𝐮𝐚𝐫𝐲.  It's been an excited year, and we can't wait to ship more stuff for you in 2025. Happy New Year!

🎉 Thrilled to share that Container Runtime for Snowflake Notebooks is now in public preview! GPUs, no problem! Snowflake is making it easier than ever before to build and deploy models while using distributed GPUs, all from a single platform. Check out the blog to learn more:

Self-hosted LLMs apps across devices! Learn to leverage fully open source #WasmEdge, #LlamaEdge, and #GaiaNet to deploy LLMs cross GPUs/ OSes. Watch our demos on setting up, customizing #LLMs with #RAG+ provide an API server in fully portable wasm file https://lnkd.in/gCT8TsBf