metadata
license: apache-2.0
library_name: diffusers
pipeline_tag: text-to-video
tags:
- wan
- echo-memory
- world-model
- community-pipeline
Echo-Memory Diffusers pipeline
Community pipeline that overlays the Echo-Memory context_k1 row onto official Wan 2.1 1.3B Diffusers weights.
- Paper: arXiv:2606.09803
- Code: Echo-Team-Joy-Future-Academy-JD/Echo-Memory
- Original keys: Echo-Team/Echo-Memory
context_k1/epoch-0.safetensors - Converted transformer: this repo,
context_k1-diffusers/diffusion_pytorch_model.safetensors
This is not the full multi-chunk camera-action / SSM research stack. It is the released DiT fine-tune remapped to Diffusers names (825 / 825 official Wan 1.3B transformer keys).
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import export_to_video
pipe = DiffusionPipeline.from_pretrained(
"Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
custom_pipeline="Wayne-King/echo-memory-diffusers",
torch_dtype=torch.bfloat16,
trust_remote_code=True,
)
pipe.load_echo_memory_weights() # remaps Echo-Team/Echo-Memory context_k1 on the fly
# or: pipe.load_converted_echo_memory_weights() # already-remapped transformer in this repo
pipe.to("cuda")
frames = pipe(
prompt="A golden retriever running across a sunny green field, cinematic camera follow.",
negative_prompt="blurry, static, low quality, deformed",
height=480,
width=832,
num_frames=33,
num_inference_steps=30,
guidance_scale=5.0,
).frames[0]
export_to_video(frames, "echo_memory_context_k1.mp4", fps=16)