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Show HN: Shoehorn – Quantize any model down to run on your machine

· 56天前
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AI 摘要

Working on Mac, Linux, and Windows now. I include a simple GUI to find new models and get things built and set up. It is working quite well across a few models for me. The GitHub README and DESIGN.md files go into detail of the how/why and it's working remarkably well so far. https://github.com/notactuallytreyanastasio/shoehorn Comments URL: https://news.ycombinator.com/item?id=49346135 Points: 5 # Comments: 2

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Before you download

What fits your machine?

Pick your hardware and this page scans Hugging Face's most-downloaded models for ones shoehorn can fit to your budget — ranked by the quality your memory affords. Runs entirely in your browser.

Your machine Mac — 8 GB Mac — 16 GB Mac — 24 GB Mac — 32 GB Mac — 48 GB Mac — 64 GB Mac — 96 GB Mac — 128 GB GPU — 8 GB VRAM GPU — 12 GB VRAM GPU — 16 GB VRAM GPU — 24 GB VRAM GPU — 32 GB VRAM Custom…
Conversation room 4k tokens — short chats 8k tokens — everyday use 16k tokens — long documents 32k tokens — the whole novella
Usable GPU memory, GiB
Find models
Get shoehorn

Install

shoehorn needs llama.cpp on your PATH as the inference backend (the Homebrew install pulls it in for you). Then shoehorn ui opens the local app — pick a model, press one button, chat.

brew install notactuallytreyanastasio/shoehorn/shoehorn Copy
macOSApple SiliconDownload →
Linuxx86-64 · NVIDIA or AMDDownload →
Windowsx86-64 · NVIDIADownload →

Or from source: cargo install --path . after cloning the repo. All releases.

The app

One button, your whole budget

The local web app measures your machine, streams the fit, renders the budget as a tape measure, puts a perplexity number on what the fit cost, and ends at a Chat button.

a finished fit: the tape-measure budget gauge at 99.998% used, the per-type mix, and Chat and Measure buttons the discovery card: models ranked by what your budget affords, each with a Use button
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