[breaking] bump transformers to 4.45.0 & improve ci (#7746)

* update ci

* fix

* fix

* fix

* fix

* fix

src/llamafactory/model/loader.py

@@ -19,7 +19,6 @@ import torch
 from transformers import (
     AutoConfig,
     AutoModelForCausalLM,
-    AutoModelForImageTextToText,
     AutoModelForSeq2SeqLM,
     AutoModelForTextToWaveform,
     AutoModelForVision2Seq,
@@ -30,6 +29,7 @@ from trl import AutoModelForCausalLMWithValueHead
 
 from ..extras import logging
 from ..extras.misc import count_parameters, skip_check_imports, try_download_model_from_other_hub
+from ..extras.packages import is_transformers_version_greater_than
 from .adapter import init_adapter
 from .model_utils.liger_kernel import apply_liger_kernel
 from .model_utils.misc import register_autoclass
@@ -39,6 +39,10 @@ from .model_utils.valuehead import load_valuehead_params
 from .patcher import patch_config, patch_model, patch_processor, patch_tokenizer, patch_valuehead_model
 
 
+if is_transformers_version_greater_than("4.46.0"):
+    from transformers import AutoModelForImageTextToText
+
+
 if TYPE_CHECKING:
     from transformers import PretrainedConfig, PreTrainedModel, PreTrainedTokenizer, ProcessorMixin
 
@@ -145,7 +149,10 @@ def load_model(
         else:
             if type(config) in AutoModelForVision2Seq._model_mapping.keys():  # image-text
                 load_class = AutoModelForVision2Seq
-            elif type(config) in AutoModelForImageTextToText._model_mapping.keys():  # image-text
+            elif (
+                is_transformers_version_greater_than("4.46.0")
+                and type(config) in AutoModelForImageTextToText._model_mapping.keys()
+            ):  # image-text
                 load_class = AutoModelForImageTextToText
             elif type(config) in AutoModelForSeq2SeqLM._model_mapping.keys():  # audio-text
                 load_class = AutoModelForSeq2SeqLM

src/llamafactory/model/model_utils/attention.py

@@ -18,7 +18,6 @@ from transformers.utils import is_flash_attn_2_available, is_torch_sdpa_availabl
 
 from ...extras import logging
 from ...extras.constants import AttentionFunction
-from ...extras.misc import check_version
 
 
 if TYPE_CHECKING:
@@ -36,8 +35,6 @@ def configure_attn_implementation(
     if getattr(config, "model_type", None) == "gemma2" and is_trainable:
         if model_args.flash_attn == AttentionFunction.AUTO or model_args.flash_attn == AttentionFunction.FA2:
             if is_flash_attn_2_available():
-                check_version("transformers>=4.42.4")
-                check_version("flash_attn>=2.6.3")
                 if model_args.flash_attn != AttentionFunction.FA2:
                     logger.warning_rank0("Gemma 2 should use flash attention 2, change `flash_attn` to fa2.")
                     model_args.flash_attn = AttentionFunction.FA2

src/llamafactory/model/model_utils/longlora.py

@@ -350,7 +350,7 @@ def llama_sdpa_attention_forward(
 
 
 def _apply_llama_patch() -> None:
-    check_version("transformers>=4.41.2,<4.48.0")
+    check_version("transformers>=4.43.0,<4.48.0", mandatory=True)
     LlamaAttention.forward = llama_attention_forward
     LlamaFlashAttention2.forward = llama_flash_attention_2_forward
     LlamaSdpaAttention.forward = llama_sdpa_attention_forward

src/llamafactory/model/model_utils/packing.py

@@ -43,7 +43,6 @@ import torch
 import torch.nn.functional as F
 
 from ...extras import logging
-from ...extras.misc import check_version
 from ...extras.packages import is_transformers_version_greater_than
 
 
@@ -117,6 +116,5 @@ def configure_packing(model_args: "ModelArguments", is_trainable: bool) -> None:
     if not is_trainable or not model_args.block_diag_attn:
         return
 
-    check_version("transformers>=4.43.0")
     transformers.modeling_flash_attention_utils._get_unpad_data = get_unpad_data
     logger.info_rank0("Using block diagonal attention for sequence packing without cross-attention.")