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Duplicate from joyfox/Wan2.1-Fight-LoRA

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Co-authored-by: YESHEN <starsfriday@users.noreply.huggingface.co>

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1
+ ---
2
+ license: apache-2.0
3
+ language:
4
+ - en
5
+ base_model:
6
+ - Wan-AI/Wan2.1-I2V-14B-720P
7
+ - Wan-AI/Wan2.1-I2V-14B-720P-Diffusers
8
+ pipeline_tag: image-to-video
9
+ tags:
10
+ - text-to-image
11
+ - lora
12
+ - diffusers
13
+ - template:diffusion-lora
14
+ widget:
15
+ - text: >-
16
+ dajia,这是一个两个人对打得视频,镜头拉远,保持人物不变,这两个人开始对打,两个人不断旋转,拳打脚踢,姿势像是传统武术,
17
+ 十分专业,两个人相互比试,打的有来有回,突然左边的人腾空跳起,保持飞在空中用腿不停踢另一个人上半身,
18
+ 男人被踢得一边用手阻挡女人的飞踢一边后退,镜头跟随,保持背景和人物的服装不改变.
19
+ output:
20
+ url: result/people_fight1.mp4
21
+ - text: >-
22
+ dajia,这是一对情侣对打得视频,镜头拉远,保持人物不变,这两个人开始对打,两个人不断旋转,拳打脚踢,姿势像是传统武术,
23
+ 十分专业,两个人相互比试,打的有来有回,突然左边的人腾空跳起,保持飞在空中用腿不停踢另一个人上半身,
24
+ 男人被踢得一边用手阻挡女人的飞踢一边后退,镜头跟随,保持背景和人物的服装不改变。
25
+ output:
26
+ url: result/people_fight2.mp4
27
+ - text: >-
28
+ dajia,这是一对闺蜜对打得视频,镜头拉远,保持人物不变,这两个人开始对打,两个人不断旋转,拳打脚踢,姿势像是传统武术,
29
+ 十分专业,两个人相互比试,打的有来有回,突然右边的人腾空跳起,保持飞在空中用腿不停踢另一个人上半身,
30
+ 右边的女人被踢得一边用手阻挡女人的飞踢一边后退,镜头跟随,保持背景和人物的服装不改变。
31
+ output:
32
+ url: result/people_fight3.mp4
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+
34
+ ---
35
+ <div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
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+ <h1 style="color: #24292e; margin-top: 0;">valiantcat LoRA for Wan2.1 14B I2V 720p</h1>
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+
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+ <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
39
+ <h2 style="color: #24292e; margin-top: 0;">Overview</h2>
40
+ <p>This LoRA is trained on the Wan2.1 14B I2V 720p model.</p>
41
+ </div>
42
+
43
+ <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
44
+ <h2 style="color: #24292e; margin-top: 0;">Features</h2>
45
+ <ul style="margin-bottom: 0;">
46
+ <li>Transform any image into a video of two people began to fight</li>
47
+ <li>Trained on the Wan2.1 14B 720p I2V base model</li>
48
+ <li>Consistent results across different object types</li>
49
+ <li>Simple prompt structure that's easy to adapt</li>
50
+ </ul>
51
+ </div>
52
+
53
+ <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
54
+ <h2 style="color: #24292e; margin-top: 0;">Community</h2>
55
+ <ul style="margin-bottom: 0;">
56
+ <li>
57
+ <b>Company:</b>
58
+ <a href="https://www.vvicat.com/" style="color: #0366d6; text-decoration: none;">
59
+ Join us to generate interesting video models together
60
+ </a> to generate videos with this LoRA for free
61
+ </li>
62
+ </ul>
63
+ </div>
64
+
65
+ <Gallery />
66
+
67
+ # Model File and Inference Workflow
68
+
69
+ ## 📥 Download Links:
70
+
71
+ - [wan2.1-fight.safetensors](./wan2.1-fight.safetensors) - LoRA Model File
72
+ - [wan_img2video_lora_workflow.json](./result/wanvideo_720p_I2V.json) - Wan I2V with LoRA Workflow for ComfyUI
73
+
74
+ ## Using with Diffusers
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+ ```py
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+ pip install git+https://github.com/huggingface/diffusers.git
77
+ ```
78
+
79
+ ```py
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+ import torch
81
+ from diffusers.utils import export_to_video, load_image
82
+ from diffusers import AutoencoderKLWan, WanImageToVideoPipeline
83
+ from transformers import CLIPVisionModel
84
+ import numpy as np
85
+
86
+ model_id = "Wan-AI/Wan2.1-I2V-14B-720P-Diffusers"
87
+ image_encoder = CLIPVisionModel.from_pretrained(model_id, subfolder="image_encoder", torch_dtype=torch.float32)
88
+ vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
89
+ pipe = WanImageToVideoPipeline.from_pretrained(model_id, vae=vae, image_encoder=image_encoder, torch_dtype=torch.bfloat16)
90
+ pipe.to("cuda")
91
+
92
+ pipe.load_lora_weights("valiantcat/Wan2.1-Fight-LoRA")
93
+
94
+ pipe.enable_model_cpu_offload() #for low-vram environments
95
+
96
+ prompt = "dajia,这是一个两个人对打得视频,镜头拉远,保持人物不变,这两个人开始对打,两个人不断旋转,拳打脚踢,姿势像是传统武术, 十分专业,两个人相互比试,打的有来有回,突然左边的人腾空跳起,保持飞在空中用腿不停踢另一个人上半身, 男人被踢得一边用手阻挡女人的飞踢一边后退,镜头跟随,保持背景和人物的服装不改变."
97
+
98
+ image = load_image("https://huggingface.co/valiantcat/Wan2.1-Fight-LoRA/blob/main/result/test.jpg")
99
+
100
+ max_area = 512 * 768
101
+ aspect_ratio = image.height / image.width
102
+ mod_value = pipe.vae_scale_factor_spatial * pipe.transformer.config.patch_size[1]
103
+ height = round(np.sqrt(max_area * aspect_ratio)) // mod_value * mod_value
104
+ width = round(np.sqrt(max_area / aspect_ratio)) // mod_value * mod_value
105
+ image = image.resize((width, height))
106
+
107
+ output = pipe(
108
+ image=image,
109
+ prompt=prompt,
110
+ height=height,
111
+ width=width,
112
+ num_frames=81,
113
+ guidance_scale=5.0,
114
+ num_inference_steps=25
115
+ ).frames[0]
116
+ export_to_video(output, "output.mp4", fps=16)
117
+ ```
118
+
119
+ ---
120
+ <div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
121
+ <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
122
+ <h2 style="color: #24292e; margin-top: 0;">Recommended Settings</h2>
123
+ <ul style="margin-bottom: 0;">
124
+ <li><b>LoRA Strength:</b> 1.0</li>
125
+ <li><b>Embedded Guidance Scale:</b> 6.0</li>
126
+ <li><b>Flow Shift:</b> 5.0</li>
127
+ </ul>
128
+ </div>
129
+
130
+ <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
131
+ <h2 style="color: #24292e; margin-top: 0;">Trigger Words</h2>
132
+ <p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">dajia</code></p>
133
+ </div>
134
+
135
+ <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
136
+ <h2 style="color: #24292e; margin-top: 0;">Prompt Template</h2>
137
+ <p>For best results, use this prompt structure:</p>
138
+ <div style="background-color: #f0f0f0; padding: 12px; border-radius: 6px; margin: 10px 0;">
139
+ <i>dajia,这是[object]对打得视频,镜头拉远,保持人物不变,这两个人开始对打,两个人不断旋转,拳打脚踢,姿势像是传统武术,十分专业,两个人相互比试,打的有来有回,突然左边的人腾空跳起,保持飞在空中用腿不停踢另一个人上半身,男人被踢得一边用手阻挡女人的飞踢一边后退,镜头跟随,保持背景和人物的服装不改变。</i>
140
+ </div>
141
+ <p>Simply replace <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">[object]</code> with whatever you want to let these two people fight!</p>
142
+ </div>
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+ {
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+ "target_modules": [
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+ "ffn.0",
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+ "k",
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+ "v",
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+ "o",
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+ "ffn.2",
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+ "k_img",
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+ "q",
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+ "v_img"
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+ }
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+ "Adjust the blocks to swap based on your VRAM, this is a tradeoff between speed and memory usage.\n\nAlternatively there's option to use VRAM management introduced in DiffSynt-Studios. This is usually slower, but saves even more VRAM compared to BlockSwap"
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+ "type": "VRAM_MANAGEMENTARGS",
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+ "Node name for S&R": "WanVideoVRAMManagement"
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+ "properties": {},
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+ "fp8_fast seems to cause huge quality degradation\n\nfp_16_fast enables \"Full FP16 Accmumulation in FP16 GEMMs\" feature available in the very latest pytorch nightly, this is around 20% speed boost. \n\nSageattn if you have it installed can be used for almost double inference speed"
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+ "Models:\nhttps://huggingface.co/Kijai/WanVideo_comfy/tree/main"
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+ "color": "#432",
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+ "You can also use native ComfyUI text encoding with these nodes instead of the original, the models are node specific and can't otherwise be mixed."
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+ "The original code had automatic resolution adjustment based on input image total pixels and aspect ratio. If you want to set it manually, disable the adjust_resolution"
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+ "Enhance-a-video can increase the fidelity of the results, too high values lead to noisy results."
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+ ],
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+ "color": "#432",
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+ "TeaCache could be considered to be sort of an automated step skipper \n\nThe relative l1 threshold -value determines how aggressive this is, higher values are faster but quality suffers more. Very first steps should NEVER be skipped with this model or it kills the motion. When using the pre-calculated coefficients, the treshold value should be much higher than with the default coefficients."
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+ ],
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+ "color": "#432",
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+ "If you have Triton installed, connect this for ~30% speed increase"
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+ "Node name for S&R": "WanVideoTorchCompileSettings"
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