File size: 1,315 Bytes
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license: apache-2.0
tags:
- video-generation
- streaming
- WaveForcing
base_model:
- Wan-AI/Wan2.1-T2V-1.3B
pipeline_tag: text-to-video
---
# WaveForcing-1.3B
Inference weights of the WaveForcing 1.3B text-to-video model, as native-Wan `model.safetensors`. Two variants: `5step/` (5 denoising steps) and `4step/` (4 denoising steps).
Text encoder, tokenizer and VAE are not included; load them from [Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B-Diffusers).
## Download
```bash
hf download SJTU-DENG-Lab/WaveForcing-1.3B --local-dir ckpts/WaveForcing-1.3B
```
## Run (WaveRT)
5-step:
```bash
python -m wave_rt \
--model-path ckpts/Wan2.1-T2V-1.3B-Diffusers \
--gen-ckpt ckpts/WaveForcing-1.3B/5step/model.safetensors \
--rf-step 5 --wp-size 6 \
--denoising-step-list 1000,800,600,400,200 \
--vae-stages 2 --vae-partition time \
--kv-context causal --exchange-mode paged \
--attention-backend torch_sdpa
```
4-step: point `--gen-ckpt` to `4step/model.safetensors` and use `--rf-step 4 --wp-size 5 --denoising-step-list 1000,750,500,250 --vae-stages 3`.
Code: [SJTU-DENG-Lab/WaveForcing](https://github.com/SJTU-DENG-Lab/WaveForcing)
Project Page: [Wave Forcing](https://sjtu-deng-lab.github.io/WaveForcing/)
Paper: [2611.00859](https://huggingface.co/papers/2611.00859) |