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Duplicate from lightx2v/Wan2.2-Distill-Models
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- .gitattributes +35 -0
- README.md +224 -0
- config.json +14 -0
- wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step.safetensors +3 -0
- wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030.safetensors +3 -0
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- wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/diffusion_pytorch_model.safetensors.index.json +1502 -0
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- wan2.2_i2v_A14b_high_noise_lightx2v_4step_720p_260412.safetensors +3 -0
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| 1 |
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---
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| 2 |
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license: apache-2.0
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tags:
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| 4 |
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- diffusion-single-file
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| 5 |
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- comfyui
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- distillation
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- LoRA
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- video
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- video genration
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base_model:
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- Wan-AI/Wan2.2-I2V-A14B
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pipeline_tags:
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- image-to-video
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- text-to-video
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library_name: diffusers
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---
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# 🎬 Wan2.2 Distilled Models
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| 18 |
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| 19 |
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### ⚡ High-Performance Video Generation with 4-Step Inference
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*Distillation-accelerated version of Wan2.2 - Dramatically faster speed with excellent quality*
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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---
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| 26 |
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| 27 |
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[](https://huggingface.co/lightx2v/Wan2.2-Distill-Models)
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| 28 |
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[](https://github.com/ModelTC/LightX2V)
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| 29 |
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[](LICENSE)
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| 31 |
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---
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| 32 |
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| 33 |
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## 🔥 News
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| 34 |
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- 2026.04.12: We are excited to release the [Wan2.2-I2V-A14B-4step-720p-high](https://huggingface.co/lightx2v/Wan2.2-Distill-Models/blob/main/wan2.2_i2v_A14b_high_noise_lightx2v_4step_720p_260412.safetensors) and [Wan2.2-I2V-A14B-4step-720p-low](https://huggingface.co/lightx2v/Wan2.2-Distill-Models/blob/main/wan2.2_i2v_A14b_low_noise_lightx2v_4step_720p_260412.safetensors) models. Compared to previous iterations, this version was trained on a high-quality 720p dataset and features an optimized low-noise training algorithm. These enhancements significantly boost the model's performance in fine-grained detail rendering and visual texture.
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| 37 |
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## 🌟 What's Special?
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| 39 |
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<table>
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<tr>
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<td width="50%">
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| 43 |
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### ⚡ Ultra-Fast Generation
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| 45 |
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- **4-step inference** (vs traditional 50+ steps)
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- Approximately **2x faster** using LightX2V than ComfyUI
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| 47 |
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- Near real-time video generation capability
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| 48 |
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</td>
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<td width="50%">
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| 51 |
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### 🎯 Flexible Options
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| 53 |
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- **Dual noise control**: High/Low noise variants
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| 54 |
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- Multiple precision formats (BF16/FP8/INT8)
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| 55 |
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- Full 14B parameter models
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| 56 |
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</td>
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</tr>
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<tr>
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<td width="50%">
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| 61 |
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| 62 |
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### 💾 Memory Efficient
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| 63 |
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- FP8/INT8: **~50% size reduction**
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| 64 |
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- CPU offload support
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| 65 |
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- Optimized for consumer GPUs
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| 66 |
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</td>
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| 68 |
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<td width="50%">
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| 69 |
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| 70 |
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### 🔧 Easy Integration
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| 71 |
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- Compatible with LightX2V framework
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| 72 |
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- ComfyUI support
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| 73 |
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- Simple configuration files
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| 74 |
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| 75 |
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</td>
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| 76 |
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</tr>
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</table>
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| 78 |
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| 79 |
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---
|
| 80 |
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| 81 |
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## 📦 Model Catalog
|
| 82 |
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| 83 |
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### 🎥 Model Types
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| 84 |
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| 85 |
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<table>
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| 86 |
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<tr>
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| 87 |
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<td align="center" width="50%">
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| 88 |
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| 89 |
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#### 🖼️ **Image-to-Video (I2V) - 14B Parameters**
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| 90 |
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Transform static images into dynamic videos with advanced quality control
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| 91 |
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| 92 |
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- 🎨 **High Noise**: More creative, diverse outputs
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| 93 |
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- 🎯 **Low Noise**: More faithful to input, stable outputs
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| 94 |
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| 95 |
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</td>
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| 96 |
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<td align="center" width="50%">
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| 97 |
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#### 📝 **Text-to-Video (T2V) - 14B Parameters**
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| 99 |
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Generate videos from text descriptions
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| 100 |
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| 101 |
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- 🎨 **High Noise**: More creative, diverse outputs
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| 102 |
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- 🎯 **Low Noise**: More stable and controllable outputs
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| 103 |
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- 🚀 Full 14B parameter model
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| 104 |
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| 105 |
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</td>
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</tr>
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</table>
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| 108 |
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| 109 |
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### 🎯 Precision Versions
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| 110 |
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| 111 |
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| Precision | Model Identifier | Model Size | Framework | Quality vs Speed |
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| 112 |
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|:---------:|:-----------------|:----------:|:---------:|:-----------------|
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| 113 |
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| 🏆 **BF16** | `lightx2v_4step` | ~28.6 GB | LightX2V | ⭐⭐⭐⭐⭐ Highest Quality |
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| 114 |
+
| ⚡ **FP8** | `scaled_fp8_e4m3_lightx2v_4step` | ~15 GB | LightX2V | ⭐⭐⭐⭐ Excellent Balance |
|
| 115 |
+
| 🎯 **INT8** | `int8_lightx2v_4step` | ~15 GB | LightX2V | ⭐⭐⭐⭐ Fast & Efficient |
|
| 116 |
+
| 🔷 **FP8 ComfyUI** | `scaled_fp8_e4m3_lightx2v_4step_comfyui` | ~15 GB | ComfyUI | ⭐⭐⭐ ComfyUI Ready |
|
| 117 |
+
|
| 118 |
+
### 📝 Naming Convention
|
| 119 |
+
|
| 120 |
+
```bash
|
| 121 |
+
# Format: wan2.2_{task}_A14b_{noise_level}_{precision}_lightx2v_4step.safetensors
|
| 122 |
+
|
| 123 |
+
# I2V Examples:
|
| 124 |
+
wan2.2_i2v_A14b_high_noise_lightx2v_4step.safetensors # I2V High Noise - BF16
|
| 125 |
+
wan2.2_i2v_A14b_high_noise_scaled_fp8_e4m3_lightx2v_4step.safetensors # I2V High Noise - FP8
|
| 126 |
+
wan2.2_i2v_A14b_low_noise_int8_lightx2v_4step.safetensors # I2V Low Noise - INT8
|
| 127 |
+
wan2.2_i2v_A14b_low_noise_scaled_fp8_e4m3_lightx2v_4step_comfyui.safetensors # I2V Low Noise - FP8 ComfyUI
|
| 128 |
+
|
| 129 |
+
```
|
| 130 |
+
> 💡 **Browse All Models**: [View Full Model Collection →](https://huggingface.co/lightx2v/Wan2.2-Distill-Models/tree/main)
|
| 131 |
+
|
| 132 |
+
---
|
| 133 |
+
|
| 134 |
+
## 🚀 Usage
|
| 135 |
+
|
| 136 |
+
### Method 1: LightX2V (Recommended ⭐)
|
| 137 |
+
|
| 138 |
+
**LightX2V is a high-performance inference framework optimized for these models, approximately 2x faster than ComfyUI with better quantization accuracy. Highly recommended!**
|
| 139 |
+
|
| 140 |
+
#### Quick Start
|
| 141 |
+
|
| 142 |
+
1. Download model (using I2V FP8 as example)
|
| 143 |
+
```bash
|
| 144 |
+
huggingface-cli download lightx2v/Wan2.2-Distill-Models \
|
| 145 |
+
--local-dir ./models/wan2.2_i2v \
|
| 146 |
+
--include "wan2.2_i2v_A14b_high_noise_scaled_fp8_e4m3_lightx2v_4step.safetensors"
|
| 147 |
+
```
|
| 148 |
+
|
| 149 |
+
```bash
|
| 150 |
+
huggingface-cli download lightx2v/Wan2.2-Distill-Models \
|
| 151 |
+
--local-dir ./models/wan2.2_i2v \
|
| 152 |
+
--include "wan2.2_i2v_A14b_low_noise_scaled_fp8_e4m3_lightx2v_4step.safetensors"
|
| 153 |
+
```
|
| 154 |
+
|
| 155 |
+
> 💡 **Tip**: For T2V models, follow the same steps but replace `i2v` with `t2v` in the filenames
|
| 156 |
+
|
| 157 |
+
2. Clone LightX2V repository
|
| 158 |
+
|
| 159 |
+
```bash
|
| 160 |
+
git clone https://github.com/ModelTC/LightX2V.git
|
| 161 |
+
cd LightX2V
|
| 162 |
+
```
|
| 163 |
+
|
| 164 |
+
3. Install dependencies
|
| 165 |
+
|
| 166 |
+
```bash
|
| 167 |
+
pip install -r requirements.txt
|
| 168 |
+
```
|
| 169 |
+
Or refer to [Quick Start Documentation](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/getting_started/quickstart.html) to use docker
|
| 170 |
+
|
| 171 |
+
4. Select and modify configuration file
|
| 172 |
+
|
| 173 |
+
Choose appropriate configuration based on your GPU memory:
|
| 174 |
+
|
| 175 |
+
**80GB+ GPUs (A100/H100)**
|
| 176 |
+
- I2V: [wan_moe_i2v_distill.json](https://github.com/ModelTC/LightX2V/blob/main/configs/wan22/wan_moe_i2v_distill.json)
|
| 177 |
+
|
| 178 |
+
**24GB+ GPUs (RTX 4090)**
|
| 179 |
+
- I2V: [wan_moe_i2v_distill_4090.json](https://github.com/ModelTC/LightX2V/blob/main/configs/wan22/wan_moe_i2v_distill_4090.json)
|
| 180 |
+
|
| 181 |
+
|
| 182 |
+
5. Run inference (using [I2V]((https://github.com/ModelTC/LightX2V/blob/main/scripts/wan22/run_wan22_moe_i2v_distill.sh)) as example)
|
| 183 |
+
```bash
|
| 184 |
+
cd scripts
|
| 185 |
+
bash wan22/run_wan22_moe_i2v_distill.sh
|
| 186 |
+
```
|
| 187 |
+
|
| 188 |
+
> 📝 **Note**: Update model paths in the script to point to your Wan2.2 model. Also refer to [LightX2V Model Structure Documentation](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/getting_started/model_structure.html)
|
| 189 |
+
|
| 190 |
+
|
| 191 |
+
#### LightX2V Documentation
|
| 192 |
+
- **Quick Start Guide**: [LightX2V Quick Start](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/getting_started/quickstart.html)
|
| 193 |
+
- **Complete Usage Guide**: [LightX2V Model Structure Documentation](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/getting_started/model_structure.html)
|
| 194 |
+
- **Configuration File Instructions**: [Configuration Files](https://github.com/ModelTC/LightX2V/tree/main/configs/distill)
|
| 195 |
+
- **Quantized Model Usage**: [Quantization Documentation](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/method_tutorials/quantization.html)
|
| 196 |
+
- **Parameter Offloading**: [Offload Documentation](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/method_tutorials/offload.html)
|
| 197 |
+
|
| 198 |
+
---
|
| 199 |
+
|
| 200 |
+
### Method 2: ComfyUI
|
| 201 |
+
|
| 202 |
+
Please refer to [workflow](https://huggingface.co/lightx2v/Wan2.2-Distill-Models/blob/main/wan2.2_moe_i2v_scale_fp8_comfyui.json)
|
| 203 |
+
|
| 204 |
+
|
| 205 |
+
|
| 206 |
+
## ⚠️ Important Notes
|
| 207 |
+
|
| 208 |
+
**Other Components**: These models only contain DIT weights. Additional components needed at runtime:
|
| 209 |
+
- T5 text encoder
|
| 210 |
+
- CLIP vision encoder
|
| 211 |
+
- VAE encoder/decoder
|
| 212 |
+
- Tokenizer
|
| 213 |
+
|
| 214 |
+
Please refer to [LightX2V Documentation](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/getting_started/model_structure.html) for instructions on organizing the complete model directory.
|
| 215 |
+
|
| 216 |
+
|
| 217 |
+
## 🤝 Community
|
| 218 |
+
|
| 219 |
+
- **GitHub Issues**: https://github.com/ModelTC/LightX2V/issues
|
| 220 |
+
- **HuggingFace**: https://huggingface.co/lightx2v/Wan2.2-Distill-Models
|
| 221 |
+
|
| 222 |
+
If you find this project helpful, please give us a ⭐ on [GitHub](https://github.com/ModelTC/LightX2V)
|
| 223 |
+
|
| 224 |
+
</div>
|
config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_class_name": "WanModel",
|
| 3 |
+
"_diffusers_version": "0.33.0",
|
| 4 |
+
"dim": 5120,
|
| 5 |
+
"eps": 1e-06,
|
| 6 |
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"ffn_dim": 13824,
|
| 7 |
+
"freq_dim": 256,
|
| 8 |
+
"in_dim": 36,
|
| 9 |
+
"model_type": "i2v",
|
| 10 |
+
"num_heads": 40,
|
| 11 |
+
"num_layers": 40,
|
| 12 |
+
"out_dim": 16,
|
| 13 |
+
"text_len": 512
|
| 14 |
+
}
|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step.safetensors
ADDED
|
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|
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|
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|
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|
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ADDED
|
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ADDED
|
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ADDED
|
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ADDED
|
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|
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|
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ADDED
|
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ADDED
|
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wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/block_20.safetensors
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|
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ADDED
|
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|
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ADDED
|
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ADDED
|
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|
|
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|
|
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|
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|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/block_24.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/block_25.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/block_26.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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version https://git-lfs.github.com/spec/v1
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size 351881728
|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/block_27.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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size 351881728
|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/block_28.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
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| 1498 |
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"time_embedding.2.weight": "non_block.safetensors",
|
| 1499 |
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"time_projection.1.bias": "non_block.safetensors",
|
| 1500 |
+
"time_projection.1.weight": "non_block.safetensors"
|
| 1501 |
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}
|
| 1502 |
+
}
|
wan2.2_i2v_A14b_high_noise_int8_lightx2v_4step_1030_split/non_block.safetensors
ADDED
|
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version https://git-lfs.github.com/spec/v1
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|
wan2.2_i2v_A14b_high_noise_lightx2v_4step.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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wan2.2_i2v_A14b_high_noise_lightx2v_4step_1030.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
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version https://git-lfs.github.com/spec/v1
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size 28577915880
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wan2.2_i2v_A14b_high_noise_lightx2v_4step_720p_260412.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
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|
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|
| 1 |
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version https://git-lfs.github.com/spec/v1
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