A fine-tuned Gemma 4 E2B for Laya-Heart, a local web app that helps you reply in a couple's chat. Given the chat and Laya's reading of it, the model writes two candidate replies, one per line. You choose, edit and send one yourself. 297 fictional practice-exam chats from the project's train-kit (253 Chinese, 44 English). Both models drafted every chat the way the app does. The judge, Qwen3-32B-AWQ, did not know which was which and judged every pair twice with the sides swapped; ties count as half a win. The flags come from the app's own checks. They are rule-based, not reviewed by a person. Self-check: the trainer's self-check (50 chats, nine gates) passed eight gates and missed one: judge…
Independent publisher
Yunkun Song
YunkunSong
Models in Library2
Datasets in Library0
Models on Hugging Face2
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Published tasks: Text classification, Text generation.
Reported licenses: apache-2.0. Open a record to review its specific license and conditions.
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Models
Two ONNX exports of Laya-multilingual (322M parameters, built on mmBERT) used by Laya-Heart, a texting copilot for couples that runs on your own computer. Laya reads the partner's message and answers short card questions with probabilities ("Does 没事 really mean it's fine?", a danger level from 1 to 10, a hidden safety question). Both run with onnxruntime and Laya's laya-ts runtime, exactly as the app runs them. Practice exam written and labelled by teacher B (Qwen3-32B-AWQ, a different model family from the teacher that wrote the training chats). One command in the repository recomputes every number from the raw answers, or re-runs both models: npm run reproduce / npm run reproduce…