diff --git a/docs/source/en/api/pipelines/text_to_video_zero.md b/docs/source/en/api/pipelines/text_to_video_zero.md
index 6f157c668785..c6bf30fed7af 100644
--- a/docs/source/en/api/pipelines/text_to_video_zero.md
+++ b/docs/source/en/api/pipelines/text_to_video_zero.md
@@ -40,6 +40,7 @@ To generate a video from prompt, run the following Python code:
 ```python
 import torch
 from diffusers import TextToVideoZeroPipeline
+import imageio
 
 model_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
 pipe = TextToVideoZeroPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda")
diff --git a/docs/source/en/optimization/coreml.md b/docs/source/en/optimization/coreml.md
index 49ff1e9c9356..d090ef0ed3ba 100644
--- a/docs/source/en/optimization/coreml.md
+++ b/docs/source/en/optimization/coreml.md
@@ -95,7 +95,7 @@ print(f"Model downloaded at {model_path}")
 Once you have downloaded a snapshot of the model, you can test it using Apple's Python script.
 
 ```shell
-python -m python_coreml_stable_diffusion.pipeline --prompt "a photo of an astronaut riding a horse on mars" -i models/coreml-stable-diffusion-v1-4_original_packages -o </path/to/output/image> --compute-unit CPU_AND_GPU --seed 93
+python -m python_coreml_stable_diffusion.pipeline --prompt "a photo of an astronaut riding a horse on mars" -i ./models/coreml-stable-diffusion-v1-4_original_packages/original/packages -o </path/to/output/image> --compute-unit CPU_AND_GPU --seed 93
 ```
 
 Pass the path of the downloaded checkpoint with `-i` flag to the script. `--compute-unit` indicates the hardware you want to allow for inference. It must be one of the following options: `ALL`, `CPU_AND_GPU`, `CPU_ONLY`, `CPU_AND_NE`. You may also provide an optional output path, and a seed for reproducibility.