I have nothing to contribute; I’m scared of used drives. Interested to hear who folks have had good luck with though.
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You actually have a lot of options in this space. You can take the prefill engine of just about any LLM and turn it’s transformer into a classifier by lobotomizing out the decoder. You can also use a diffusion model on single pass to surprisingly competent result.
If Jeff looks easy enough to deploy by all means start there, but don’t discount the idea if Jeff sucks; you have a lot of options.
You could (and probably should) use a system-one style inference system for spam classification. Much cheaper and the structured output means it’s impossible to go rogue and curl some malware or whatever. It can absolutely misclassify but its output is programmatically structured and just ranks a pre-selected set of output tokens.
In your case that’s
Spam
Not_spam

Genuinely asking, why is it important?