Repository: huggingface/transformers
Pull request: Stop collecting all model parameters to save models when using DeepSpeed and LoRA

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Fixes #41344 


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Models:

- text models: @ArthurZucker @Cyrilvallez
- vision models: @yonigozlan @molbap
- audio models: @eustlb @ebezzam @vasqu
- multimodal models: @zucchini-nlp
- graph models: @clefourrier

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- generate: @zucchini-nlp (visual-language models) or @gante (all others)
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- deepspeed: HF Trainer/Accelerate: @SunMarc @zach-huggingface
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber
- kernels: @MekkCyber @drbh
- peft: @BenjaminBossan @githubnemo

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- AMD ROCm: @ivarflakstad
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Changed files:
filename: src/transformers/trainer.py
patch: @@ -4021,7 +4021,16 @@ def save_model(self, output_dir: str | None = None, _internal_call: bool = False
                     self._save(output_dir, state_dict=state_dict)
         elif self.is_deepspeed_enabled:
             try:
-                state_dict = self.accelerator.get_state_dict(self.deepspeed)
+                accept_exclude_frozen_parameters = "exclude_frozen_parameters" in set(
+                    inspect.signature(self.model_wrapped.save_checkpoint).parameters.keys()
+                )
+                zero3_sharding = self.deepspeed.config.get("zero_optimization", {}).get("stage", None) == 3
+                if accept_exclude_frozen_parameters and _is_peft_model(self.model) and zero3_sharding:
+                    # When using PEFT with DeepSpeed ZeRO Stage 3,
+                    # we do not need to load the frozen parameters
+                    state_dict = self.deepspeed._zero3_consolidated_16bit_state_dict(exclude_frozen_parameters=True)
+                else:
+                    state_dict = self.accelerator.get_state_dict(self.deepspeed)
                 if self.args.should_save:
                     self._save(output_dir, state_dict=state_dict)
             except ValueError: