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license: apache-2.0
library_name: diffsynth
pipeline_tag: text-to-video
tags:
- wan
- wan2.1
- echo-memory
- text-to-video
base_model: Wan-AI/Wan2.1-T2V-1.3B
---
# Echo-Memory `context_k1` — complete Wan 2.1 1.3B DiT
DiffSynth-facing **full DiT** for the released Echo-Memory `context_k1` row.
- Paper: [arXiv:2606.09803](https://arxiv.org/abs/2606.09803)
- Code: [Echo-Team-Joy-Future-Academy-JD/Echo-Memory](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory)
- Research overlay (HF): [Echo-Team/Echo-Memory](https://huggingface.co/Echo-Team/Echo-Memory) `context_k1/epoch-0.safetensors`
## What this file is
`diffusion_pytorch_model-*-of-00006.safetensors` is a **complete Wan 2.1 T2V 1.3B DiT** (825 / 825 official keys), sharded for Hub upload. Load with `origin_file_pattern="diffusion_pytorch_model*.safetensors"`.
It is official [Wan-AI/Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B) DiT keys with the Echo-Memory `context_k1` overlay already merged. Research extras (`action_mlp`, `self_attn_with_action`, SSM / spatial slots) are **not** included, so the file loads like a normal Wan transformer (`strict=True` on `pipe.dit`).
T5 and VAE stay the official Wan files:
- `Wan-AI/Wan2.1-T2V-1.3B` `models_t5_umt5-xxl-enc-bf16.pth`
- `Wan-AI/Wan2.1-T2V-1.3B` `Wan2.1_VAE.pth`
## DiffSynth
```python
import torch
from diffsynth.pipelines.wan_video import WanVideoPipeline, ModelConfig
from diffsynth.utils.data import save_video
pipe = WanVideoPipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="SOTAowner/Echo-Memory-context-k1", origin_file_pattern="diffusion_pytorch_model*.safetensors"),
ModelConfig(model_id="Wan-AI/Wan2.1-T2V-1.3B", origin_file_pattern="models_t5_umt5-xxl-enc-bf16.pth"),
ModelConfig(model_id="Wan-AI/Wan2.1-T2V-1.3B", origin_file_pattern="Wan2.1_VAE.pth"),
],
)
video = pipe(prompt="A toy bear on a table, the camera rotates around it", seed=42)
save_video(video, "echo_memory_context_k1.mp4")
```
After this repo is mirrored on ModelScope, replace the DiT `model_id` with that ModelScope id (DiffSynth downloads from ModelScope by default).
## Notes
- 30,000-step `epoch-0` fine-tune, 640×352, 81-frame chunks.
- Camera-action / multi-chunk revisit protocol stays in the Echo-Memory repo; this file is the Wan DiT overlay only.
- Apache-2.0. Please cite the Echo-Memory paper if you use it.
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