File size: 3,434 Bytes
eafbe80 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | # Checkpoints (Hugging Face)
**Repo:** [Echo-Team/Echo-Memory](https://huggingface.co/Echo-Team/Echo-Memory)
Fine-tuned DiT weights on top of [Wan-AI/Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B). Released rows are saved as `{row_id}/epoch-0.safetensors` after **1 epoch / 30,000 steps** on the static in-domain pool (640×352, 81-frame chunks). Mechanism names follow [memory_mechanisms.md](memory_mechanisms.md).
## Checkpoint index
| Family | Paper row | HF path | Steps | Echo-Memory recipe |
| --- | --- | --- | ---: | --- |
| Raw context | Context K=1 | [`context_k1/epoch-0.safetensors`](https://huggingface.co/Echo-Team/Echo-Memory/tree/main/context_k1) | 30,000 | `train/context_learning/run_pre_qkv_ctx1.sh` |
| Raw context | Context K=20 | TODO | TODO | `train/context_learning/run_pre_qkv_ctx20.sh` |
| Spatial | Spatial Memory | TODO | TODO | `train/memory_baselines_basic/run_spatial_memory_baseline.sh` |
| State-space | Block-wise SSM | TODO | TODO | `train/memory_baselines_basic/run_ablation_block_wise_ssm_two_chunk.sh` |
| State-space | Legacy Hybrid (VideoSSM) | TODO | TODO | `train/memory_baselines_basic/run_videossm_hybrid_baseline.sh` |
| Spatial | concat text (ablation) | TODO | TODO | `train/memory_baselines_basic/run_ablation_spatial_concat_text_two_chunk.sh` |
| Spatial | inject none (ablation) | TODO | TODO | `train/memory_baselines_basic/run_ablation_spatial_inject_none_two_chunk.sh` |
| Spatial | cross-attn t32 (ablation) | TODO | TODO | `train/memory_baselines_basic/run_ablation_spatial_cross_attn_readout_two_chunk.sh` |
| State-space | SSM ctx1 / every4 / hint21 | TODO | TODO | SSM ablation |
| State-space | SSM ctx5 / every1 / hint21 | TODO | TODO | SSM ablation |
| State-space | SSM ctx5 / every4 / hint81 | TODO | TODO | SSM ablation |
Context K=5, Context K=20, Spatial memory, FramePack compression, and State-space / SSM rows are TODO and not yet released as `epoch-0` weights.
## Download
```bash
pip install -U "huggingface_hub[cli]"
# one row (keeps HF folder layout under ./ckpts/)
huggingface-cli download Echo-Team/Echo-Memory context_k1/epoch-0.safetensors --local-dir ./ckpts
# all currently released rows
huggingface-cli download Echo-Team/Echo-Memory --local-dir ./ckpts
```
Keep the subdirectory name in the local path (e.g. `./ckpts/context_k1/epoch-0.safetensors`). Eval scripts use `env/memory_baseline_runtime.py` to infer memory flags from path substrings; Spatial and SSM checkpoint rows remain TODO.
## Use with Echo-Memory
Set the Wan backbone, static in-domain data pool, and checkpoint path:
```bash
export WAN_BASE_MODEL=/path/to/Wan2.1-T2V-1.3B
export DATASET_BASE_PATH=data/Context-as-Memory-Dataset
export PYTHONPATH=$PWD:${PYTHONPATH:-}
export CKPT=./ckpts/context_k1/epoch-0.safetensors
```
**In-domain replay + revisit (paper bundle):**
```bash
bash eval/v2/run_static_consistency_loop_and_revisit.sh
bash eval/v2/run_basic_replay_gt.sh
```
**Open-domain revisit** (first frames already in `assets/opendomain_revisit/`):
```bash
PHASE=stage1 OOD_DIR=assets/opendomain_revisit \
bash eval/v2/revisit_suite/run_one_click_revisit_eval.sh
```
**Visual comparison** (fixed prompt + first frame):
```bash
python eval/metrics/run_visual_eval.py \
--ckpt "$CKPT" \
--output_root ./evals_visual
```
See [eval/v2/README.md](../eval/v2/README.md) and [eval/metrics/README.md](../eval/metrics/README.md) for full options.
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