Echo Memory
Validated 30,000-step fine-tunes for Echo-Memory, built on Wan-AI/Wan2.1-T2V-1.3B.
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
| 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
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
Sources
1 sourceVerified Oct 26
Download files
Model artifacts
3 artifacts
Model artifacts
3 artifactsblock_wise_ssm_causal_v2/epoch-0.safetensors
safetensors · 3.28 GB · SHA-256 0dd90ea3f342…01a9 · Hugging Face
Download filecontext_k1/epoch-0.safetensors
safetensors · 3.17 GB · SHA-256 adf323dc903c…dbfa · Hugging Face
Download fileframepack_len_r8/epoch-0.safetensors
safetensors · 3.17 GB · SHA-256 dd57625506a2…74bf · Hugging Face
Download fileSource excerpts
3 excerpts
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
