Squish Pika Lora
About this LoRA
This is a LoRA for the Wan 14B Text-to-Video model.
It can be used with diffusers or ComfyUI, and can be loaded against the Wan 14B models.
It was trained on Replicate with 10 steps at a learning rate of 2e-05 and LoRA rank of 32.
Trigger word
You should use SQUISH-IT
to trigger the video generation.
Use this LoRA
Replicate has a collection of Wan models that are optimised for speed and cost. They can also be used with this LoRA:
Run this LoRA with an API using Replicate
import replicate
input = {
"prompt": "SQUISH-IT",
"lora_url": "https://huggingface.co/zsxkib/squish-pika-lora/resolve/main/wan-14b-t2v-squish-it-lora.safetensors"
}
output = replicate.run(
"fofr/wan-with-lora:latest",
model="14B",
input=input
)
for index, item in enumerate(output):
with open(f"output_{index}.mp4", "wb") as file:
file.write(item.read())
Using with Diffusers
import torch
from diffusers.utils import export_to_video
from diffusers import WanVidAdapter, WanVid
# Load base model
base_model = WanVid.from_pretrained("Wan-AI/Wan2.1-T2V-14B-Diffusers", torch_dtype=torch.float16)
# Load and apply LoRA adapter
adapter = WanVidAdapter.from_pretrained("zsxkib/squish-pika-lora")
base_model.load_adapter(adapter)
# Generate video
prompt = "SQUISH-IT"
negative_prompt = "blurry, low quality, low resolution"
# Generate video frames
frames = base_model(
prompt=prompt,
negative_prompt=negative_prompt,
num_inference_steps=30,
guidance_scale=5.0,
width=832,
height=480,
fps=16,
num_frames=32,
).frames[0]
# Save as video
video_path = "output.mp4"
export_to_video(frames, video_path, fps=16)
print(f"Video saved to: {video_path}")
Training details
- Steps: 10
- Learning rate: 2e-05
- LoRA rank: 32
Contribute your own examples
You can use the community tab to add videos that show off what you've made with this LoRA.
Model tree for zsxkib/squish-pika-lora
Base model
Wan-AI/Wan2.1-T2V-14B-Diffusers