BANKING77
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- Naive-N0.5-Flash automates parts of model training
New Zhiyuan reports that the open-source Naive-N0.5-Flash can handle parts of model-training workflows, including data preparation, training, evaluation, and identifying flaws in scoring rules. In a community project described by the outlet, a creator used Naive-N0.5-Flash through Claude Code to fine-tune a 0.6B model on a 24GB Mac after writing a one-page task specification. New Zhiyuan also says it used the system on a 64GB Mac to train a locally running, 110-million-parameter BERT classifier for the BANKING77 dataset. The outlet reports 93.34% accuracy on the official test set and a 6.77-millisecond median response time, while noting that the workflow still requires a human-written program.md and researcher intervention.
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