How Specializing the Vocabulary of SLMs Can Cut Inference Cost by 77% in Real Applications

Deploying small language models for narrow operational tasks often burns through cloud budgets unnecessarily because teams carry the dead weight of massive, general-purpose vocabularies. In a technical deep dive published on Hugging Face, the team at Dharma