[v1] add sft (#9752)

src/llamafactory/v1/trainers/sft_trainer.py

@@ -18,21 +18,35 @@ from ..config import InputArgument, get_args
 from ..core.base_trainer import BaseTrainer
 from ..core.data_engine import DataEngine
 from ..core.model_engine import ModelEngine
+from ..utils.types import BatchInput, Tensor
 
 
 class SFTTrainer(BaseTrainer):
-    pass
+    def compute_loss(self, batch: BatchInput) -> Tensor:
+        shift_loss_weights = batch["loss_weights"].to(self.device, non_blocking=True)[..., 1:]
+        log_probs = self.compute_log_probs(self.model, batch)
+        loss = (-log_probs * shift_loss_weights).sum() / (shift_loss_weights.sum() + 1e-6)
+        return loss
 
 
 def run_sft(args: InputArgument = None):
     model_args, data_args, training_args, _ = get_args(args)
     DistributedInterface(training_args.dist_config)
-    data_engine = DataEngine(data_args)
+    train_dataset = DataEngine(data_args.train_dataset)
     model_engine = ModelEngine(model_args)
     trainer = SFTTrainer(
         args=training_args,
         model=model_engine.model,
         renderer=model_engine.renderer,
-        dataset=data_engine,
+        train_dataset=train_dataset,
     )
     trainer.fit()
+    trainer.save_model()
+    DistributedInterface().destroy()
+
+
+if __name__ == "__main__":
+    """
+    python -m llamafactory.v1.trainers.sft_trainer --model Qwen/Qwen3-0.6B --train_dataset data/v1_sft_demo.yaml
+    """
+    run_sft()