Fix typos (#718)

* Fix typos

* Update examples/dreambooth/train_dreambooth.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

docs/source/optimization/fp16.mdx

@@ -120,7 +120,7 @@ print(pipe.unet.conv_out.state_dict()["weight"].stride())  # (2880, 9, 3, 1)
 pipe.unet.to(memory_format=torch.channels_last)  # in-place operation
 print(
     pipe.unet.conv_out.state_dict()["weight"].stride()
-)  # (2880, 1, 960, 320) haveing a stride of 1 for the 2nd dimension proves that it works
+)  # (2880, 1, 960, 320) having a stride of 1 for the 2nd dimension proves that it works
 ```
 
 ## Tracing

examples/dreambooth/README.md

@@ -62,7 +62,7 @@ accelerate launch train_dreambooth.py \
 ### Training with prior-preservation loss
 
 Prior-preservation is used to avoid overfitting and language-drift. Refer to the paper to learn more about it. For prior-preservation we first generate images using the model with a class prompt and then use those during training along with our data.
-According to the paper, it's recommened to generate `num_epochs * num_samples` images for prior-preservation. 200-300 works well for most cases.
+According to the paper, it's recommended to generate `num_epochs * num_samples` images for prior-preservation. 200-300 works well for most cases.
 
 ```bash
 export MODEL_NAME="CompVis/stable-diffusion-v1-4"

examples/dreambooth/train_dreambooth.py

@@ -58,19 +58,19 @@ def parse_args():
         "--instance_prompt",
         type=str,
         default=None,
-        help="The prompt with identifier specifing the instance",
+        help="The prompt with identifier specifying the instance",
     )
     parser.add_argument(
         "--class_prompt",
         type=str,
         default=None,
-        help="The prompt to specify images in the same class as provided intance images.",
+        help="The prompt to specify images in the same class as provided instance images.",
     )
     parser.add_argument(
         "--with_prior_preservation",
         default=False,
         action="store_true",
-        help="Flag to add prior perservation loss.",
+        help="Flag to add prior preservation loss.",
     )
     parser.add_argument("--prior_loss_weight", type=float, default=1.0, help="The weight of prior preservation loss.")
     parser.add_argument(
@@ -214,7 +214,7 @@ def parse_args():
 
 class DreamBoothDataset(Dataset):
     """
-    A dataset to prepare the instance and class images with the promots for fine-tuning the model.
+    A dataset to prepare the instance and class images with the prompts for fine-tuning the model.
     It pre-processes the images and the tokenizes prompts.
     """
 

examples/test_examples.py

@@ -40,7 +40,7 @@ class SubprocessCallException(Exception):
 def run_command(command: List[str], return_stdout=False):
     """
     Runs `command` with `subprocess.check_output` and will potentially return the `stdout`. Will also properly capture
-    if an error occured while running `command`
+    if an error occurred while running `command`
     """
     try:
         output = subprocess.check_output(command, stderr=subprocess.STDOUT)