What it does
On its RACE-H benchmark, writing each passage once for four questions cut token use 2.5-fold and raised throughput 2.3-fold.
Benchmarks & research
This open-weights Jev alternative returns typed, calibrated choices in one Hugging Face or vLLM forward pass.
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On its RACE-H benchmark, writing each passage once for four questions cut token use 2.5-fold and raised throughput 2.3-fold.
Before writing any code, gather your sample texts, such as user tickets or short passages. For each item, write down the specific questions you want answered. List the allowed choices for each question, such as urgency ratings or topic categories.
Your developer can integrate this Python package to answer all your questions about a text at the same time. Note that answering questions together can sometimes cause nearby answers to influence each other. Have your developer run questions separately if decisions must stay completely independent.