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SCM
Open models that turn text + a question into probabilities
Open-weight models that turn text + a question into a probability for every answer: choice, yes/no, or score. Self-host them: no API, no bill per call, no data leaving. Weights, sources, licences and a benchmark-overlap audit are published. Github Repo : https://github.com/5ak3t/scm
Hi, 5ak3t here, I built SCM. Thanks for stopping by.
What it is: SCM (Sovereign Classification Model) is a family of open models that do one job: you give them a text and a question, and they return a probability for every answer. Choose from your options, get yes/no, or place the text on a scale.
Why I built it: the best typed-decision models ask you to accept something. The hosted reference is accurate, but your text goes to someone else's servers and every call is billed.
The strongest open ones need 27B-class hardware. The tiny fast ones give up accuracy and some quietly train on the benchmark's own data families.
I wanted the middle: accurate enough to test, small enough to self-host, open enough to audit.
What "open" means here: the weights, every training source with its licence, the sources we excluded and why, the prompt format and scoring recipe, and an audit of how much a public benchmark overlaps our training data, all published next to the results.
The numbers, plainly: on S1MB English the 14B model completes all 137 benchmarks with zero failed decisions and scores 55.5 rank 19 of 165 by our computation. That's below the hosted Jev 1.13 reference (59.6) and below the 27B class.
If you want an open, self-hostable model whose data and evaluation you can check, that's what SCM is for.
Models: https://huggingface.co/5ak3t/scm... · https://huggingface.co/5ak3t/scm...
Questions, scepticism and benchmark gripes all welcome, I'll be here all day.
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About SCM on Product Hunt
“Open models that turn text + a question into probabilities ”
SCM was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #68 on the daily leaderboard. Open-weight models that turn text + a question into a probability for every answer: choice, yes/no, or score. Self-host them: no API, no bill per call, no data leaving. Weights, sources, licences and a benchmark-overlap audit are published. Github Repo : https://github.com/5ak3t/scm
SCM was featured in Open Source (69k followers), Developer Tools (521.5k followers), Artificial Intelligence (481.6k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 269.6k products, making this a competitive space to launch in.
Who hunted SCM?
SCM was hunted by Saket Bhushan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Saket Bhushan