diff --git a/.github/workflows/gpu_ci_test.yml b/.github/workflows/gpu_ci_test.yml index 41358fe1e..ccb0c68fc 100644 --- a/.github/workflows/gpu_ci_test.yml +++ b/.github/workflows/gpu_ci_test.yml @@ -14,7 +14,7 @@ concurrency: jobs: Test: name: Test - runs-on: [self-hosted, ernie-8gpu] + runs-on: [self-hosted, ernie-8gpu-1] steps: - name: Start Docker run: | diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml index ee001cb82..2a9149add 100644 --- a/.github/workflows/lint.yml +++ b/.github/workflows/lint.yml @@ -13,7 +13,7 @@ env: jobs: Lint: name: Lint - runs-on: [self-hosted, ernie-cpu] + runs-on: [self-hosted, ernie-cpu-01] permissions: pull-requests: write contents: read diff --git a/erniekit/train/ocr_vl_sft/trainer.py b/erniekit/train/ocr_vl_sft/trainer.py index cf606b996..0e59e20ea 100644 --- a/erniekit/train/ocr_vl_sft/trainer.py +++ b/erniekit/train/ocr_vl_sft/trainer.py @@ -39,7 +39,7 @@ from distutils.util import strtobool -from paddleformers.peft import LoRAModel, PrefixModelForCausalLM +from paddleformers.peft import LoRAModel from paddleformers.trainer import ( speed_metrics, ) @@ -833,9 +833,7 @@ def fused_allreduce_gradients_no_sync(paramlist, hcg): logger.info( f"Loading best model from {self.state.best_model_checkpoint} (score: {self.state.best_metric})." ) - if isinstance(self.model, LoRAModel) or isinstance( - self.model, PrefixModelForCausalLM - ): + if isinstance(self.model, LoRAModel): self._load_best_model_from_peft_checkpoint() else: weight_name = PADDLE_WEIGHTS_NAME diff --git a/erniekit/train/vl_sft/trainer.py b/erniekit/train/vl_sft/trainer.py index 3e3f79564..7aeba8a90 100644 --- a/erniekit/train/vl_sft/trainer.py +++ b/erniekit/train/vl_sft/trainer.py @@ -41,7 +41,7 @@ from setuptools._distutils.util import strtobool -from paddleformers.peft import LoRAModel, PrefixModelForCausalLM +from paddleformers.peft import LoRAModel from paddleformers.trainer import ( speed_metrics, ) @@ -829,9 +829,7 @@ def fused_allreduce_gradients_no_sync(paramlist, hcg): logger.info( f"Loading best model from {self.state.best_model_checkpoint} (score: {self.state.best_metric})." ) - if isinstance(self.model, LoRAModel) or isinstance( - self.model, PrefixModelForCausalLM - ): + if isinstance(self.model, LoRAModel): self._load_best_model_from_peft_checkpoint() else: weight_name = PADDLE_WEIGHTS_NAME