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AccVideo support

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DeepBeepMeep 2025-06-06 00:53:39 +02:00
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10
README.md
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@ -18,12 +18,16 @@ WanGP supports the Wan (and derived models), Hunyuan Video and LTV Video models
**Discord Server to get Help from Other Users and show your Best Videos:** https://discord.gg/g7efUW9jGV
## 🔥 Latest Updates
### May 28 2025: WanGP v5.41
👋 Bonus release: Support for **AccVideo** Lora to speed up x2 Video generations in Wan models. Check the Loras documentation to get the usage instructions of AccVideo.\
You will need to do a *pip install -r requirements.txt*
### May 28 2025: WanGP v5.4
👋 World Exclusive : Hunyuan Video Avatar Support ! You won't need 80 GB of VRAM nor 32 GB oF VRAM, just 10 GB of VRAM will be sufficient to generate up to 15s of high quality speech / song driven Video at a high speed with no quality degradation. Support for TeaCache included.\
👋 World Exclusive : **Hunyuan Video Avatar** Support ! You won't need 80 GB of VRAM nor 32 GB oF VRAM, just 10 GB of VRAM will be sufficient to generate up to 15s of high quality speech / song driven Video at a high speed with no quality degradation. Support for TeaCache included.\
Also many thanks to Reevoy24 for his repackaging / completing the documentation
### May 28 2025: WanGP v5.31
👋 Added Phantom 14B, a model that you can use to transfer objects / people in the video. My preference goes to Vace that remains the king of controlnets.
👋 Added **Phantom 14B**, a model that you can use to transfer objects / people in the video. My preference goes to Vace that remains the king of controlnets.
VACE improvements: Better sliding window transitions, image mask support in Matanyone, new Extend Video feature, and enhanced background removal options.
### May 26, 2025: WanGP v5.3
@ -33,7 +37,7 @@ VACE improvements: Better sliding window transitions, image mask support in Mata
- Export/import settings as JSON files for easy sharing and backup
### May 20, 2025: WanGP v5.2
👋 **CausVid support** - Generate videos in just 4-12 steps with the new distilled Wan model! Also added experimental MoviiGen for 1080p generation (20GB+ VRAM required).
👋 **CausVid support** - Generate videos in just 4-12 steps with the new distilled Wan model! Also added experimental MoviiGen for 1080p generation (20GB+ VRAM required). Check the Loras documentation to get the usage instructions of CausVid.
### May 18, 2025: WanGP v5.1
👋 **LTX Video 13B Distilled** - Generate high-quality videos in less than one minute!

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docs/CHANGELOG.md
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@ -1,6 +1,9 @@
# Changelog
## 🔥 Latest News
### May 28 2025: WanGP v5.41
👋 Bonus release: Support for **AccVideo** Lora to speed up x2 Video generations in Wan models. Check the Loras documentation to get the usage instructions of AccVideo.
### May 28 2025: WanGP v5.4
👋 World Exclusive : Hunyuan Video Avatar Support ! You won't need 80 GB of VRAM nor 32 GB oF VRAM, just 10 GB of VRAM will be sufficient to generate up to 15s of high quality speech / song driven Video at a high speed with no quality degradation. Support for TeaCache included.

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docs/LORAS.md
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@ -88,7 +88,7 @@ python wgp.py --lora-preset mypreset.lset
- Presets include comments with usage instructions
- Share `.lset` files with other users
## CausVid Lora (Special)
## CausVid Lora (Video Generation Accelerator)
CausVid is a distilled Wan model that generates videos in 4-12 steps with 2x speed improvement.
@ -125,6 +125,33 @@ WanGP supports multiple lora formats:
- **Replicate** format
- **Standard PyTorch** (.pt, .pth)
## AccVid Lora (Video Generation Accelerator)
AccVid is a distilled Wan model that generates videos with a 2x speed improvement since classifier free guidance is no longer needed (that is cfg = 1).
### Setup Instructions
1. Download the CausVid Lora:
- for t2v models:
```
https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan21_AccVid_T2V_14B_lora_rank32_fp16.safetensors
```
- for i2v models:
```
https://huggingface.co/Kijai/WanVideo_comfy/blob/main/Wan21_AccVid_I2V_480P_14B_lora_rank32_fp16.safetensors
```
2. Place in your `loras/` directory or `loras_i2v/` directory
### Usage
1. Select a Wan t2v model (e.g., Wan 2.1 text2video 13B or Vace 13B) or Wan i2v model
2. Enable Advanced Mode
3. In Advanced Generation Tab:
- Set Guidance Scale = 1
- Set Shift Scale = 5
4. The number steps remain unchanged compared to what you would use with the original model but it will be two times faster since classifier free guidance is not needed
## Performance Tips
### Fast Loading/Unloading

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requirements.txt
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@ -17,7 +17,7 @@ gradio==5.23.0
numpy>=1.23.5,<2
einops
moviepy==1.0.3
mmgp==3.4.7
mmgp==3.4.8
peft==0.14.0
mutagen
pydantic==2.10.6