Jev vs SemIf
SemIf reads option probabilities from an open model you already run. It does not train a new Jev.
What SemIf is
SemIf, by TheoLeeCJ, is MIT-licensed. An earlier name for the same project was OpenJev. It does not fine-tune. It takes a frozen open LLM, scores the options you declared from that model's logits, and returns a distribution. You can fit a temperature per workload.
You bring the model
You need the base model and a machine that can run it. People have used it from small GPUs up to larger Qwen-class models. The quality follows the model you attach. There is no separate Jev checkpoint inside SemIf.
When it fits
Use SemIf when you already host an open LLM and you want typed decisions without a second vendor. Use JEV Gateway when you want a hosted Jev call and you do not want to run the weights.