[deps] upgrade transformers to 4.50.0 (#7437)

* upgrade transformers

* fix hf cache

* fix dpo trainer

requirements.txt

@@ -1,5 +1,5 @@
-transformers>=4.41.2,<=4.49.0,!=4.46.*,!=4.47.*,!=4.48.*;python_version<'3.10'
-transformers>=4.41.2,<=4.49.0,!=4.46.*,!=4.47.*,!=4.48.0;python_version>='3.10'
+transformers>=4.41.2,<=4.50.0,!=4.46.*,!=4.47.*,!=4.48.*;python_version<'3.10'
+transformers>=4.41.2,<=4.50.0,!=4.46.*,!=4.47.*,!=4.48.0;python_version>='3.10'
 datasets>=2.16.0,<=3.3.2
 accelerate>=0.34.0,<=1.4.0
 peft>=0.11.1,<=0.12.0

src/llamafactory/__init__.py

@@ -19,7 +19,7 @@ Level:
 
 Dependency graph:
   main:
-    transformers>=4.41.2,<=4.49.0,!=4.46.*,!=4.47.*,!=4.48.0
+    transformers>=4.41.2,<=4.50.0,!=4.46.*,!=4.47.*,!=4.48.0
     datasets>=2.16.0,<=3.3.2
     accelerate>=0.34.0,<=1.4.0
     peft>=0.11.1,<=0.12.0

src/llamafactory/data/parser.py

@@ -17,7 +17,7 @@ import os
 from dataclasses import dataclass
 from typing import Any, Literal, Optional
 
-from transformers.utils import cached_file
+from huggingface_hub import hf_hub_download
 
 from ..extras.constants import DATA_CONFIG
 from ..extras.misc import use_modelscope, use_openmind
@@ -99,7 +99,7 @@ def get_dataset_list(dataset_names: Optional[list[str]], dataset_dir: str) -> li
         dataset_info = None
     else:
         if dataset_dir.startswith("REMOTE:"):
-            config_path = cached_file(path_or_repo_id=dataset_dir[7:], filename=DATA_CONFIG, repo_type="dataset")
+            config_path = hf_hub_download(repo_id=dataset_dir[7:], filename=DATA_CONFIG, repo_type="dataset")
         else:
             config_path = os.path.join(dataset_dir, DATA_CONFIG)
 

src/llamafactory/extras/misc.py

@@ -88,7 +88,7 @@ def check_version(requirement: str, mandatory: bool = False) -> None:
 
 def check_dependencies() -> None:
     r"""Check the version of the required packages."""
-    check_version("transformers>=4.41.2,<=4.49.0,!=4.46.0,!=4.46.1,!=4.46.2,!=4.46.3,!=4.47.0,!=4.47.1,!=4.48.0")
+    check_version("transformers>=4.41.2,<=4.50.0,!=4.46.0,!=4.46.1,!=4.46.2,!=4.46.3,!=4.47.0,!=4.47.1,!=4.48.0")
     check_version("datasets>=2.16.0,<=3.3.2")
     check_version("accelerate>=0.34.0,<=1.4.0")
     check_version("peft>=0.11.1,<=0.12.0")

src/llamafactory/train/dpo/trainer.py

@@ -128,9 +128,9 @@ class CustomDPOTrainer(DPOTrainer):
         return super()._get_train_sampler()
 
     @override
-    def get_batch_samples(self, epoch_iterator, num_batches):
+    def get_batch_samples(self, epoch_iterator, num_batches, *args, **kwargs):
         r"""Replace the method of DPO Trainer with the one of the standard Trainer."""
-        return Trainer.get_batch_samples(self, epoch_iterator, num_batches)
+        return Trainer.get_batch_samples(self, epoch_iterator, num_batches, *args, **kwargs)
 
     def odds_ratio_loss(self, chosen_logps: "torch.Tensor", rejected_logps: "torch.Tensor") -> "torch.Tensor":
         r"""Compute ORPO's odds ratio (OR) loss for batched log probabilities of the policy model."""

src/llamafactory/train/kto/trainer.py

@@ -127,9 +127,9 @@ class CustomKTOTrainer(KTOTrainer):
         return Trainer._get_train_sampler(self)
 
     @override
-    def get_batch_samples(self, epoch_iterator, num_batches):
+    def get_batch_samples(self, epoch_iterator, num_batches, *args, **kwargs):
         r"""Replace the method of KTO Trainer with the one of the standard Trainer."""
-        return Trainer.get_batch_samples(self, epoch_iterator, num_batches)
+        return Trainer.get_batch_samples(self, epoch_iterator, num_batches, *args, **kwargs)
 
     @override
     def forward(