fix fsdp model loading

src/llmtuner/model/patcher.py

@@ -6,6 +6,7 @@ import torch
 from peft import PeftModel
 from transformers import PreTrainedModel, PreTrainedTokenizerBase, is_torch_npu_available
 from transformers.integrations import is_deepspeed_zero3_enabled
+from transformers.modeling_utils import is_fsdp_enabled
 
 from ..extras.logging import get_logger
 from ..extras.misc import infer_optim_dtype
@@ -69,7 +70,7 @@ def patch_config(
         setattr(config, "use_cache", False)  # qwen2 does not support use_cache when using flashattn
 
     init_kwargs["torch_dtype"] = model_args.compute_dtype
-    if not is_deepspeed_zero3_enabled():
+    if not is_deepspeed_zero3_enabled() and not is_fsdp_enabled():
         init_kwargs["low_cpu_mem_usage"] = model_args.low_cpu_mem_usage
         if init_kwargs["low_cpu_mem_usage"]:
             if "device_map" not in init_kwargs and model_args.device_map:

src/llmtuner/model/utils/quantization.py

@@ -7,6 +7,7 @@ import torch
 from datasets import load_dataset
 from transformers import BitsAndBytesConfig, GPTQConfig
 from transformers.integrations import is_deepspeed_zero3_enabled
+from transformers.modeling_utils import is_fsdp_enabled
 from transformers.utils.versions import require_version
 
 from ...extras.constants import FILEEXT2TYPE
@@ -133,7 +134,7 @@ def configure_quantization(
                 bnb_4bit_quant_storage=model_args.compute_dtype,  # crucial for fsdp qlora
             )
 
-        if is_deepspeed_zero3_enabled() or model_args.quantization_device_map == "auto":
+        if is_deepspeed_zero3_enabled() or is_fsdp_enabled() or model_args.quantization_device_map == "auto":
             if model_args.quantization_bit != 4:
                 raise ValueError("Only 4-bit quantized model can use auto device map.")