

“Since the dataset isn’t 100% perfectly annotated for analysis, we should give up the whole project entirely.”


https://ollama.ai/, this is what I’ve been using for over a year now, new models come out regularly and you just “ollama pull <model ID>” and then it’s available to run locally. Then you can use docker to run https://www.openwebui.com/ locally, giving it a ChatGPT-style interface (but even better and more configurable and you can run prompts against any number of models you select at once.)
All free and available to everyone.


In my experience it depends on the math. Every model seems to have different strengths based on a wide berth of prompts and information.


+1 for Mistral, they were the first (or one of the first) Apache open source licensed models. I run Mistral-7B and variant fine tunes locally, and they’ve always been really high quality overall. Mistral-Medium packed a punch (mid-size obviously) but it definitely competes with the big ones at least.
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