diff --git a/docs/source/en/api/pipelines/animatediff.md b/docs/source/en/api/pipelines/animatediff.md
index ff621c60221d..cb379c1a8349 100644
--- a/docs/source/en/api/pipelines/animatediff.md
+++ b/docs/source/en/api/pipelines/animatediff.md
@@ -88,6 +88,128 @@ AnimateDiff tends to work better with finetuned Stable Diffusion models. If you
+## Using Motion LoRAs
+
+Motion LoRAs are a collection of LoRAs that work with the `guoyww/animatediff-motion-adapter-v1-5-2` checkpoint. These LoRAs are responsible for adding specific types of motion to the animations.
+
+```python
+import torch
+from diffusers import MotionAdapter, AnimateDiffPipeline, DDIMScheduler
+from diffusers.utils import export_to_gif
+
+# Load the motion adapter
+adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2")
+# load SD 1.5 based finetuned model
+model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
+pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter)
+pipe.load_lora_weights("guoyww/animatediff-motion-lora-zoom-out", adapter_name="zoom-out")
+
+scheduler = DDIMScheduler.from_pretrained(
+ model_id, subfolder="scheduler", clip_sample=False, timestep_spacing="linspace", steps_offset=1
+)
+pipe.scheduler = scheduler
+
+# enable memory savings
+pipe.enable_vae_slicing()
+pipe.enable_model_cpu_offload()
+
+output = pipe(
+ prompt=(
+ "masterpiece, bestquality, highlydetailed, ultradetailed, sunset, "
+ "orange sky, warm lighting, fishing boats, ocean waves seagulls, "
+ "rippling water, wharf, silhouette, serene atmosphere, dusk, evening glow, "
+ "golden hour, coastal landscape, seaside scenery"
+ ),
+ negative_prompt="bad quality, worse quality",
+ num_frames=16,
+ guidance_scale=7.5,
+ num_inference_steps=25,
+ generator=torch.Generator("cpu").manual_seed(42),
+)
+frames = output.frames[0]
+export_to_gif(frames, "animation.gif")
+```
+
+
+
+
+ masterpiece, bestquality, sunset.
+
+
+ |
+
+
+
+## Using Motion LoRAs with PEFT
+
+You can also leverage the [PEFT](https://github.com/huggingface/peft) backend to combine Motion LoRA's and create more complex animations.
+
+First install PEFT with
+
+```shell
+pip install peft
+```
+
+Then you can use the following code to combine Motion LoRAs.
+
+```python
+
+```python
+import torch
+from diffusers import MotionAdapter, AnimateDiffPipeline, DDIMScheduler
+from diffusers.utils import export_to_gif
+
+# Load the motion adapter
+adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-2")
+# load SD 1.5 based finetuned model
+model_id = "SG161222/Realistic_Vision_V5.1_noVAE"
+pipe = AnimateDiffPipeline.from_pretrained(model_id, motion_adapter=adapter)
+
+pipe.load_lora_weights("diffusers/animatediff-motion-lora-zoom-out", adapter_name="zoom-out")
+pipe.load_lora_weights("diffusers/animatediff-motion-lora-pan-left", adapter_name="pan-left")
+pipe.set_adapters(["zoom-out", "pan-left"], adapter_weights=[1.0, 1.0])
+
+scheduler = DDIMScheduler.from_pretrained(
+ model_id, subfolder="scheduler", clip_sample=False, timestep_spacing="linspace", steps_offset=1
+)
+pipe.scheduler = scheduler
+
+# enable memory savings
+pipe.enable_vae_slicing()
+pipe.enable_model_cpu_offload()
+
+output = pipe(
+ prompt=(
+ "masterpiece, bestquality, highlydetailed, ultradetailed, sunset, "
+ "orange sky, warm lighting, fishing boats, ocean waves seagulls, "
+ "rippling water, wharf, silhouette, serene atmosphere, dusk, evening glow, "
+ "golden hour, coastal landscape, seaside scenery"
+ ),
+ negative_prompt="bad quality, worse quality",
+ num_frames=16,
+ guidance_scale=7.5,
+ num_inference_steps=25,
+ generator=torch.Generator("cpu").manual_seed(42),
+)
+frames = output.frames[0]
+export_to_gif(frames, "animation.gif")
+```
+
+
+
+
+ masterpiece, bestquality, sunset.
+
+
+ |
+
+
+
+
## AnimateDiffPipeline
[[autodoc]] AnimateDiffPipeline
- all