depot.ai – easily embed ML / AI models in your Dockerfile
Hey HN! We're excited to launch https://depot.ai today - depot.ai is an open-source Docker registry that makes it easy to embed public models from Hugging Face in your Docker images using a `COPY`: # Copy all files from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 / . # COPY just one file from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 /v1-5-pruned.ckpt . To optimize build speed, cache hits, and registry storage, we're building each image…
What it does
In the maker’s words, at launch
Hey HN! We're excited to launch https://depot.ai today - depot.ai is an open-source Docker registry that makes it easy to embed public models from Hugging Face in your Docker images using a `COPY`: # Copy all files from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 / . # COPY just one file from the model repo to the current WORKDIR COPY --link --from=depot.ai/runwayml/stable-diffusion-v1-5 /v1-5-pruned.ckpt . To optimize build speed, cache hits, and registry storage, we're building each image reproducibly and indexing the contents with eStargz[0]. The image is stored on Cloudflare R2, and served via a Cloudflare Worker. Everything is open source[1]! Compared to alternatives like `git lfs clone` or downloading your model at runtime, embedding it with `COPY` produces layers that are cache-stable, with identical hash digests across rebuilds. This means they can be fully cached, even if your base image or source code changes. And for Docker builders that enable eStargz, copying single files from the image will download only the requested files. eStargz can be enabled in a variety of image builders[2], and we’ve enabled it by default on Depot[3]. Here’s an announcement post with more details: https://depot.dev/blog/depot-ai. We’d love to hear any feedback you may have! [0] https://github.com/containerd/stargz-snapshotter/blob/main/docs/estargz.md [1] https://github.com/depot/depot.ai [2] https://github.com/containerd/stargz-snapshotter/blob/main/docs/integration.md#image-builders [3] https://depot.dev
Does the same job
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, July 2023
the whole month →
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Hey everyone, I here is a small open-source project I've been working on lately. I'd love to hear your thoughts and improvement ideas :) GitHub: [github.com/Vincenius/workout-lol](https://github.com/Vincenius/workout-lol)
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- HN
I saw this [0] pretty cool thread by user revskill, and wanted a quicker way to search through it, but also to keep them all in one place so I can read them at my leisure whenever I get time. Right now is like 60 lines of Ruby using Nokogiri, but I will certainly look into it further down the line and improve the list. There's a cronjob checking the thread every 12 hours but I will eventually shut that down and it will become static after that. There are some really awesome blogs in there. I really recommend going through the list, it made my day. [0] "Could you share your personal blog…
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A safe space for your thoughts, private, local, p2p & open
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