fix

Author: stevhliu

docs/source/en/using-diffusers/batched_inference.md

@@ -89,9 +89,15 @@ for i, image in enumerate(images):
 
 Enable reproducible batch generation by passing a list of [Generator’s](https://pytorch.org/docs/stable/generated/torch.Generator.html) to the pipeline and tie each `Generator` to a seed to reuse it.
 
-Use a list comprehension to iterate over the batch size specified in `range()` to create a unique `Generator` object for each image in the batch. Don't multiply the `Generator` by the batch size because that only creates one `Generator` object that is used sequentially for each image in the batch.
+Use a list comprehension to iterate over the batch size specified in `range()` to create a unique `Generator` object for each image in the batch.
 
-Pass the `geneator` to the pipeline.
+Don't multiply the `Generator` by the batch size because that only creates one `Generator` object that is used sequentially for each image in the batch.
+
+```py
+generator = [torch.Generator(device="cuda").manual_seed(0)] * 3
+```
+
+Pass the `generator` to the pipeline.
 
 ```py
 import torch