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README.md

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+---
+base_model: enochlev/MiniCPM-duplex
+tags:
+- full-duplex
+- speech
+- turn-taking
+- reinforcement-learning
+---
+
+# MiniCPM-duplex-rl
+
+RL-trained **full-duplex** conversational model tuned for natural turn-taking — the training
+goal is to **avoid interrupting the user** while still responding promptly once they finish.
+
+- **Base:** [enochlev/MiniCPM-duplex](https://huggingface.co/enochlev/MiniCPM-duplex)
+- **Method:** REINFORCE over turn-taking reward functions (interruption penalty, timely-response
+  reward, idle/silence shaping). This checkpoint is seed 2 ("run9"), best avg_reward +1.35.
+- **Serving:** text-only full-duplex server (`server.py --cpm`), ~1.7 s decision blocks,
+  monotonic ASR commit.
+
+## Evaluation (FullDuplexBench)
+
+Scored with GPT-4o behavior classification over ~90–175 real conversations per task. On the
+"don't interrupt" objective (lower RESPOND / higher RESUME = interrupts less), this seed
+interrupts less than the base — and less than an independent same-config seed — on 3 of 4 tasks
+(largest gains on `background_speech` and `talking_to_other`; `user_backchannel` already at floor).