hugging-face

Fine tuning pays off when domain language differs from general web text and you have enough labeled examples to justify it. I keep the training recipe conservative: class weighting if needed, early stopping, mixed precision when available, and metrics

I use transformers when the text task justifies contextual modeling and the serving budget can handle it. The fastest path to value is usually starting with pretrained checkpoints, measuring latency, and then deciding whether quantization, distillatio