[AnimateLCM](https://animatelcm.github.io/) is a motion module checkpoint and an [LCM LoRA](https://huggingface.co/docs/diffusers/using-diffusers/inference_with_lcm_lora) that have been created using a consistency learning strategy that decouples the distillation of the image generation priors and the motion generation priors.  
```python
import torch
from diffusers import AnimateDiffPipeline, LCMScheduler, MotionAdapter
from diffusers.utils import export_to_gif

adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM")
pipe = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, beta_schedule="linear")

pipe.load_lora_weights("wangfuyun/AnimateLCM", weight_name="sd15_lora_beta.safetensors", adapter_name="lcm-lora")

pipe.enable_vae_slicing()
pipe.enable_model_cpu_offload()

output = pipe(
prompt="A space rocket with trails of smoke behind it launching into space from the desert, 4k, high resolution",
negative_prompt="bad quality, worse quality, low resolution",
num_frames=16,
guidance_scale=1.5,
num_inference_steps=6,
generator=torch.Generator("cpu").manual_seed(0),
)
frames = output.frames[0]
export_to_gif(frames, "animatelcm.gif")
```  
<table>
<tr>
<td><center>
A space rocket, 4K.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatelcm-output.gif"
alt="A space rocket, 4K"
style="width: 300px;" />
</center></td>
</tr>
</table>  
AnimateLCM is also compatible with existing [Motion LoRAs](https://huggingface.co/collections/dn6/animatediff-motion-loras-654cb8ad732b9e3cf4d3c17e).  
```python
import torch
from diffusers import AnimateDiffPipeline, LCMScheduler, MotionAdapter
from diffusers.utils import export_to_gif

adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM")
pipe = AnimateDiffPipeline.from_pretrained("emilianJR/epiCRealism", motion_adapter=adapter)
pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, beta_schedule="linear")

pipe.load_lora_weights("wangfuyun/AnimateLCM", weight_name="sd15_lora_beta.safetensors", adapter_name="lcm-lora")
pipe.load_lora_weights("guoyww/animatediff-motion-lora-tilt-up", adapter_name="tilt-up")

pipe.set_adapters(["lcm-lora", "tilt-up"], [1.0, 0.8])
pipe.enable_vae_slicing()
pipe.enable_model_cpu_offload()

output = pipe(
prompt="A space rocket with trails of smoke behind it launching into space from the desert, 4k, high resolution",
negative_prompt="bad quality, worse quality, low resolution",
num_frames=16,
guidance_scale=1.5,
num_inference_steps=6,
generator=torch.Generator("cpu").manual_seed(0),
)
frames = output.frames[0]
export_to_gif(frames, "animatelcm-motion-lora.gif")
```  
<table>
<tr>
<td><center>
A space rocket, 4K.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/animatelcm-motion-lora.gif"
alt="A space rocket, 4K"
style="width: 300px;" />
</center></td>
</tr>
</table>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/animatediff.md