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erikkaumย 
posted an update 5 months ago
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ZML just released a technical preview of their new Inference Engine: LLMD.

- Just 2.4GB container, which means fast startup times and efficient autoscaling
- Cross-Platform GPU Support: works on both NVIDIA and AMD GPUs.
- written in Zig

I just tried it out and deployed it on Hugging Face Inference Endpoints and wrote a quick guide ๐Ÿ‘‡ You can try it in like 5 minutes!

https://huggingface.co/blog/erikkaum/test-driving-llmd-inference-engine
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erikkaumย 
posted an update 5 months ago
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2133
We just released native support for @SGLang and @vllm-project in Inference Endpoints ๐Ÿ”ฅ

Inference Endpoints is becoming the central place where you deploy high performance Inference Engines.

And that provides the managed infra for it. Instead of spending weeks configuring infrastructure, managing servers, and debugging deployment issues, you can focus on what matters most: your AI model and your users ๐Ÿ™Œ
florentgbelidjiย 
posted an update 12 months ago
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1875
๐—ฃ๐—น๐—ฎ๐—ป๐—ป๐—ถ๐—ป๐—ด ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ก๐—ฒ๐˜…๐˜ ๐—ฆ๐—ธ๐—ถ ๐—”๐—ฑ๐˜ƒ๐—ฒ๐—ป๐˜๐˜‚๐—ฟ๐—ฒ ๐—๐˜‚๐˜€๐˜ ๐—š๐—ผ๐˜ ๐—ฆ๐—บ๐—ฎ๐—ฟ๐˜๐—ฒ๐—ฟ: ๐—œ๐—ป๐˜๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐—ถ๐—ป๐—ด ๐—”๐—น๐—ฝ๐—ถ๐—ป๐—ฒ ๐—”๐—ด๐—ฒ๐—ป๐˜!๐Ÿ”๏ธโ›ท๏ธ

With the big hype around AI agents these days, I couldnโ€™t stop thinking about how AI agents could truly enhance real-world activities.
What sort of applications could we build with those AI agents: agentic RAG? self-correcting text-to-sql? Nah, boringโ€ฆ

Passionate about outdoors, Iโ€™ve always dreamed of a tool that could simplify planning mountain trips while accounting for all potential risks. Thatโ€™s why I built ๐—”๐—น๐—ฝ๐—ถ๐—ป๐—ฒ ๐—”๐—ด๐—ฒ๐—ป๐˜, a smart assistant designed to help you plan safe and enjoyable itineraries in the French Alps and Pyrenees.

Built using Hugging Face's ๐˜€๐—บ๐—ผ๐—น๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€ library, Alpine Agent combines the power of AI with trusted resources like ๐˜š๐˜ฌ๐˜ช๐˜ต๐˜ฐ๐˜ถ๐˜ณ.๐˜ง๐˜ณ (https://skitour.fr/) and METEO FRANCE. Whether itโ€™s suggesting a route with moderate difficulty or analyzing avalanche risks and weather conditions, this agent dynamically integrates data to deliver personalized recommendations.

In my latest blog post, I share how I developed this projectโ€”from defining tools and integrating APIs to selecting the best LLMs like ๐˜˜๐˜ธ๐˜ฆ๐˜ฏ2.5-๐˜Š๐˜ฐ๐˜ฅ๐˜ฆ๐˜ณ-32๐˜‰-๐˜๐˜ฏ๐˜ด๐˜ต๐˜ณ๐˜ถ๐˜ค๐˜ต, ๐˜“๐˜ญ๐˜ข๐˜ฎ๐˜ข-3.3-70๐˜‰-๐˜๐˜ฏ๐˜ด๐˜ต๐˜ณ๐˜ถ๐˜ค๐˜ต, or ๐˜Ž๐˜—๐˜›-4.

โ›ท๏ธ Curious how AI can enhance adventure planning?โ€จTry the app and share your thoughts: florentgbelidji/alpine-agent

๐Ÿ‘‰ Want to build your own agents? Whether for cooking, sports training, or other passions, the possibilities are endless. Check out the blog post to learn more: https://huggingface.co/blog/florentgbelidji/alpine-agent

Many thanks to @m-ric for helping on building this tool with smolagents!
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erikkaumย 
posted an update about 1 year ago
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1808
A while ago I started experimenting with compiling the Python interpreter to WASM.

To build a secure, fast, and lightweight sandbox for code execution โ€” ideal for running LLM-generated Python code.

- Send code simply as a POST request
- 1-2ms startup times

Hack away:
https://github.com/ErikKaum/runner