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Echo Memory

Validated 30,000-step fine-tunes for Echo-Memory, built on Wan-AI/Wan2.1-T2V-1.3B.

KindOtherBase modelWan-AI/Wan2.1-T2V-1.3BVersionRevision b69a600Publisher@Echo-TeamCgrade

Model source

Kind
Other
File size
3.17–3.28 GB
Base model
Wan-AI/Wan2.1-T2V-1.3B
Version
vRevision b69a600
Updated
Oct 26, 2026
Publisher
@Echo-Team
Downloads
0
Source
Hugging Face

Source description

Echo-Memory — Wan 2.1 1.3B memory checkpoints

Validated 30,000-step fine-tunes for Echo-Memory, built on Wan-AI/Wan2.1-T2V-1.3B.

Paper · Project page · Code · Interactive demo · Dataset

Try the model in the browser (ZeroGPU, no local GPU): hugging-apps/echo-memory

Available checkpoints

FamilyCheckpointStepsSHA256
Raw contextcontext_k1/epoch-0.safetensors30,000See LFS metadata
Compressionframepack_len_r8/epoch-0.safetensors30,000dd57625506a2c68c402dc05de8f3c6fc5f5376fcac77d7fb6f26eb6ace1d74bf
State-spaceblock_wise_ssm_causal_v2/epoch-0.safetensors30,0000dd90ea3f3423644f4d68c6d1185d7d717d328f5922ee21f745fc85abe9a01a9

MoC, geometry-grounded spatial memory, legacy SSM, and VideoSSM weights are not part of this validated release.

Download

huggingface-cli download Echo-Team/Echo-Memory \
  block_wise_ssm_causal_v2/epoch-0.safetensors \
  framepack_len_r8/epoch-0.safetensors \
  --local-dir ./ckpts

Keep the row folder in the local path. Echo-Memory auto-detects the profile and restores the trained context order, FramePack strategy, and camera-RT continuation.

Multi-chunk inference

export WAN_BASE_MODEL=/path/to/Wan2.1-T2V-1.3B
export CONTEXT_IMAGE=/path/to/first_frame.png
export ACTION_PATH=/path/to/81_frame_camera_action.json

CKPT=./ckpts/block_wise_ssm_causal_v2/epoch-0.safetensors NUM_CHUNKS=4 \
  bash inference/memory_baselines_basic/run_infer_block_wise_ssm_causal_v2.sh

CKPT=./ckpts/framepack_len_r8/epoch-0.safetensors NUM_CHUNKS=4 \
  bash inference/memory_baselines_basic/run_infer_framepack_len_r8.sh

Citation

@article{king2026echomemory,
  title={Echo-Memory: A Controlled Study of Memory in Action World Models},
  author={King, Wayne and Xue, Zeyue and Bian, Yuxuan and Huang, Jie and Li, Haoran and Li, Yaowei and Su, Yaofeng and Li, Yuming and Wang, Haoyu and Zhang, Shiyi and Zhang, Songchun and Niu, Yuwei and Xu, Sihan and Zhuang, Junhao and Huang, Haoyang and Duan, Nan},
  journal={arXiv preprint arXiv:2606.09803},
  year={2026}
}

Sources

1 source
Hugging FacePrimaryVersion b69a600860cc8ddd781f11aac9ed5a5bf491cddc
huggingface.co/Echo-Team/Echo-Memory/tree/b69a600860cc8ddd781f11aac9ed5a5bf491cddc

Verified Oct 26

Download files

Model artifacts

3 artifacts

block_wise_ssm_causal_v2/epoch-0.safetensors

safetensors · 3.28 GB · SHA-256 0dd90ea3f342…01a9 · Hugging Face

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context_k1/epoch-0.safetensors

safetensors · 3.17 GB · SHA-256 adf323dc903c…dbfa · Hugging Face

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framepack_len_r8/epoch-0.safetensors

safetensors · 3.17 GB · SHA-256 dd57625506a2…74bf · Hugging Face

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Source excerpts

3 excerpts

--- language: - en library_name: diffsynth license: cc-by-4.0 pipeline_tag: image-to-video base_model: - Wan-AI/Wan2.1-T2V-1.3B arxiv: 2606.09803 tags: - video-generation - world-model - memory - action-conditioned - wan - image-to-video --- # Echo-Memory — Wan 2.1 1.3B memory checkpoints Validated **30,000-step** fine-tunes for [Echo-Memory](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory), built on [Wan-AI/Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B). [Paper](https://huggingface.co/papers/2606.09803) · [Project page](https://echo-team-joy-future-academy-jd.github.io/Echo-Memory/) · [Code](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory) · [**Interactive demo**](https://huggingface.co/spaces/hugging-apps/echo-memory) · [Dataset](https://huggingface.co/datasets/Echo-Team/Echo-Memory-Data) Try the model in the browser (ZeroGPU, no local GPU): **[hugging-apps/echo-memory](https://huggingface.co/spaces/hugging-apps/echo-memory)** ## Available checkpoints | Family | Checkpoint | Steps | SHA256 | | --- | --- | ---: | --- | | Raw context | `context_k1/epoch-0.safetensors` | 30,000 | See LFS metadata | | Compression | `framepack_len_r8/epoch-0.safetensors` | 30,000 | `dd57625506a2c68c402dc05de8f3c6fc5f5376fcac77d7fb6f26eb6ace1d74bf` | | State-space | `block_wise_ssm_causal_v2/epoch-0.safetensors` | 30,000 | `0dd90ea3f3423644f4d68c6d1185d7d717d328f5922ee21f745fc85abe9a01a9` | MoC, geometry-grounded spatial memory, legacy SSM, and VideoSSM weights are not part of this validated release. ## Download ```bash huggingface-cli download Echo-Team/Echo-Memory \ block_wise_ssm_causal_v2/epoch-0.safetensors \ framepack_len_r8/epoch-0.safetensors \ --local-dir ./ckpts ``` Keep the row folder in the local path. Echo-Memory auto-detects the profile and restores the trained context order, FramePack strategy, and camera-RT continuation. ## Multi-chunk inference ```bash export WAN_BASE_MODEL=/path/to/Wan2.1-T2V-1.3B export CONTEXT_IMAGE=/path/to/first_frame.png export ACTION_PATH=/path/to/81_frame_camera_action.json CKPT=./ckpts/block_wise_ssm_causal_v2/epoch-0.safetensors NUM_CHUNKS=4 \ bash inference/memory_baselines_basic/run_infer_block_wise_ssm_causal_v2.sh CKPT=./ckpts/framepack_len_r8/epoch-0.safetensors NUM_CHUNKS=4 \ bash inference/memory_baselines_basic/run_infer_framepack_len_r8.sh ``` ## Citation `...

--- language: - en library_name: diffsynth license: cc-by-4.0 pipeline_tag: image-to-video tags: - video-generation - world-model - memory - action-conditioned - wan --- # Echo-Memory — Wan 2.1 1.3B memory baseline checkpoints Paper-aligned **epoch-0** fine-tunes for [Echo-Memory](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory). [**Paper**](https://huggingface.co/papers/2606.09803) | [**Project Page**](https://echo-team-joy-future-academy-jd.github.io/Echo-Memory/) | [**GitHub**](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory) **Backbone:** [Wan-AI/Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B) **Training:** static in-domain pool · 1 epoch · **30,000 steps** · 640×352 · 81-frame chunks **Layout:** `{row_id}/epoch-0.safetensors` ## Checkpoint index | Family | Paper row | HF path | Steps | | --- | --- | --- | ---: | | Raw context | Context K=1 | `context_k1/epoch-0.safetensors` | 30,000 | | Raw context | Context K=20 | `context_k20/epoch-0.safetensors` | 30,000 | | Spatial | Spatial Memory | `spatial_mem/epoch-0.safetensors` | 30,000 | | State-space | Block-wise SSM | `block_wise_ssm_two_chunk/epoch-0.safetensors` | 30,000 | | State-space | Legacy Hybrid (VideoSSM) | `videossm_hybrid/epoch-0.safetensors` | 30,000 | | Spatial | concat text (ablation) | `spatial_concat_text_two_chunk/epoch-0.safetensors` | 30,000 | | Spatial | inject none (ablation) | `spatial_inject_none_two_chunk/epoch-0.safetensors` | 30,000 | | Spatial | cross-attn t32 (ablation) | `spatial_cross_attn_readout_t32_g4_two_chunk/epoch-0.safetensors` | 30,000 | | State-space | SSM ctx1 / every4 / hint21 | `ssm_ablation_ctx1_every4_hint21/epoch-0.safetensors` | 30,000 | | State-space | SSM ctx5 / every1 / hint21 | `ssm_ablation_ctx5_every1_hint21/epoch-0.safetensors` | 30,000 | | State-space | SSM ctx5 / every4 / hint81 | `ssm_ablation_ctx5_every4_hint81/epoch-0.safetensors` | 30,000 | Context K=5 and FramePack compression rows are not yet released as `epoch-0` weights. ## Download ```bash pip install -U "huggingface_hub[cli]" # one row huggingface-cli download Echo-Team/Echo-Memory context_k1/epoch-0.safetensors --local-dir ./ckpts # all rows huggingface-cli download Echo-Team/Echo-Memory --local-dir ./ckpts ``` Keep the row subdirectory in the local path (e.g. `./ckpts/spatial_mem/epoch-0.safetensors`). ## Use with Echo-Memory cod...

Source context: 0 downloads · 2 likes · Pipeline image-to-video · Library diffsynth · Repo Echo-Team/Echo-Memory