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docs/source/reward_trainer.md

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@@ -191,7 +191,7 @@ trainer = RewardTrainer(
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trainer.train()
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```
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You can also continue training your [`peft.PeftModel`]. For that, first load a `PeftModel` outside [`RewardTrainer`] and pass it directly to the trainer without the `peft_config` argument being passed.
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You can also continue training your [`~peft.PeftModel`]. For that, first load a `PeftModel` outside [`RewardTrainer`] and pass it directly to the trainer without the `peft_config` argument being passed.
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```python
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from datasets import load_dataset

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