Add support for `torch_dtype` in the run_mlm example (#29776)

feat: add support for torch_dtype
Co-authored-by: Jacky Lee <jackylee328@gmail.com>

examples/pytorch/language-modeling/run_mlm.py

@@ -32,6 +32,7 @@ from typing import Optional
 
 import datasets
 import evaluate
+import torch
 from datasets import load_dataset
 
 import transformers
@@ -133,6 +134,16 @@ class ModelArguments:
             )
         },
     )
+    torch_dtype: Optional[str] = field(
+        default=None,
+        metadata={
+            "help": (
+                "Override the default `torch.dtype` and load the model under this dtype. If `auto` is passed, the "
+                "dtype will be automatically derived from the model's weights."
+            ),
+            "choices": ["auto", "bfloat16", "float16", "float32"],
+        },
+    )
     low_cpu_mem_usage: bool = field(
         default=False,
         metadata={
@@ -425,6 +436,11 @@ def main():
         )
 
     if model_args.model_name_or_path:
+        torch_dtype = (
+            model_args.torch_dtype
+            if model_args.torch_dtype in ["auto", None]
+            else getattr(torch, model_args.torch_dtype)
+        )
         model = AutoModelForMaskedLM.from_pretrained(
             model_args.model_name_or_path,
             from_tf=bool(".ckpt" in model_args.model_name_or_path),
@@ -433,6 +449,7 @@ def main():
             revision=model_args.model_revision,
             token=model_args.token,
             trust_remote_code=model_args.trust_remote_code,
+            torch_dtype=torch_dtype,
             low_cpu_mem_usage=model_args.low_cpu_mem_usage,
         )
     else: