<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/9a1271fadf0c4291b263ed8b6bc3a8cb&quot; frameborder=&quot;0&quot; width=&quot;1108&quot; height=&quot;831&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>831</height><width>1108</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>831</thumbnail_height><thumbnail_width>1108</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/9a1271fadf0c4291b263ed8b6bc3a8cb-2776014db3a6693f.gif</thumbnail_url><duration>300.027</duration><title>Self-hosted batching code walkthrough</title><description>I was left with some really interesting prompts around running evals on self-hosted models, and took some time to dig into (1) how self-hosting works and (2) how to address the unique scaling problems you hit with self-hosting. To say the least, I was nerdsniped.

This is part 2 of a 3 part walkthrough. This part covers the meat and potatoes of it, but if you&apos;d like you&apos;re more than welcome to chat out the other clips!
- Part 1: https://www.loom.com/share/003d4facf2254098b4fde8a09f0840d3
- Part 2: This video!
- Part 3: https://www.loom.com/share/ddba1d3f42a64f279a64092bcc2829a5</description></oembed>