UnifiedHorusRA commited on
Commit
dca9634
ยท
verified ยท
1 Parent(s): 4ae4d1c

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +130 -0
README.md ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language:
3
+ - en
4
+ tags:
5
+ - art
6
+ ---
7
+
8
+ # Live Wallpaper Style
9
+
10
+ **Creator**: [NRDX](https://civitai.com/user/NRDX)
11
+ **Type**: LORA
12
+ **Base Model**: Wan Video 2.2 TI2V-5B
13
+ **Version**: Wan2.2 TI2V 5B 720P
14
+ **Trigger Words**: `l1v3w4llp4p3r`
15
+
16
+ **Civitai Model ID**: 1264662
17
+ **Civitai Version ID**: 2080103
18
+
19
+ **Stats (at time of fetch for this version)**:
20
+ * Downloads: 978
21
+ * Rating: 0 (0 ratings)
22
+ * Favorites: N/A
23
+
24
+ ---
25
+
26
+ ## ๐Ÿ“„ Description (Parent Model)
27
+
28
+ The goal of this lora is to reproduce the video style similar to live wallpaper, for those who play league of legends remember the launcher opening videos, that's the goal, but you can also use it to create your lofi videos :D enjoy.
29
+ [Wan2.2 TI2V 5B - Motion Optimized Edition]
30
+ Trained on 51 curated videos (24fps, 96 frames) for 5,000 steps across 100 epochs with rank 48. Optimized specifically for Wan2.2's unified TI2V 5B dense model and high-compression VAE.
31
+ My Workflow (It's not organized, the important thing is that it works hahaha):
32
+ ๐ŸŽฎ Live Wallpaper LoRA - Wan2.2 5B (Workflow) | Patreon
33
+ Trigger word:
34
+ l1v3w4llp4p3r
35
+ [Wan2.2 I2V A14B - Full Timestep Edition]
36
+ Trained on 301 curated videos (256px, 16fps, 49 frames) for 24 hours using Diffusion Pipe with Automagic optimizer, rank 64. Uses extended timestep range (0-1) instead of standard (0-0.875), enabling compatibility with both Low and High models despite training only on Low model.
37
+ Trigger word:
38
+ l1v3w4llp4p3r
39
+ Works excellently with LightX2V v2 (256 rank) for faster inference - recommended starting strength: 2.0 for both LoRAs to avoid artifacts. Loop workflows not yet tested.
40
+ [Wan I2V 720P Fast Fusion - 4 (or more) steps]
41
+ Wan I2V 720P Fast Fusion combines 2 Live Wallpaper LoRA (1 Exclusive) with Lightx2v, AccVid, MoviiGen and Pusa LoRAs for ultra-fast 4+ steps generation while maintaining cinematic quality.
42
+ ๐Ÿš€
43
+ Lightx2v LoRA
44
+ โ€“ accelerates generation by 20x through 4-step distillation, enabling sub 2-minute videos on RTX 4090 with only 8GB VRAM requirements.
45
+ ๐ŸŽฌ
46
+ AccVid LoRA
47
+ โ€“ improves motion accuracy and dynamics for expressive sequences.
48
+ ๐ŸŒŒ
49
+ MoviiGen LoRA
50
+ โ€“ adds cinematic depth and flow to animation, enhancing visual storytelling.
51
+ ๐Ÿง 
52
+ Pusa LoRA
53
+ โ€“ provides fine-grained temporal control with zero-shot multi-task capabilities (start-end frames, video extension) while achieving 87.32% VBench score.
54
+ ๐Ÿง 
55
+ Wan I2V 720p (14B)
56
+ base model โ€“ providing strong temporal consistency and high-resolution outputs for expressive video scenes.
57
+ [Wan I2V 720P]
58
+ The dataset used consists of 149 videos (each one hand-selected) in 1280x720x96 resolution but was trained in 244p and 480p and 64 frames with 64 dim (L40s).
59
+ Trigger word was used so it needs to be included in the prompt:
60
+ l1v3w4llp4p3r
61
+ [Hunyuan T2V]
62
+ The dataset used consists of 529 videos (each one hand-selected) in 1280x720x96 resolution but was trained in 244p and 72 frames with 64 dim (multiple RTX 4090).
63
+ No captions or activation words were used, the only control you will need to adjust is the lora strength.
64
+ Another important note is that it was trained in full blocks, I don't know how it will behave when mixing 2 or more loras, if you want to mix and are not getting a good result, try disabling single blocks.
65
+ I recommend using lora strength between 0.2 and 1.2 maximum, resolution 1280x720 or generate at 512 and upscale later, minimum 3 seconds (72 frames + 1).
66
+ [LTXV I2V 13b 0.9.7 โ€“ Experimental v1]
67
+ The model was trained on 140 curated videos (512px, 24fps, 49 frames), using 250 epochs, 32 dim, and AdamW8bit.
68
+ It was trained using Diffusion Pipe with support for LTXV I2V v0.9.7 (13B).
69
+ Captions were used and generated with Qwen2.5-VL-7B via a structured prompt format.
70
+ This is an
71
+ experimental first version
72
+ , so expect some variability depending on seed and prompt detail.
73
+ Recommended:
74
+ Scheduler: sgm_uniform
75
+ Sampler: euler
76
+ Steps: 30
77
+ โš ๏ธ Long prompts are highly recommended to avoid motion artifacts.
78
+ You can generate captions using the
79
+ Ollama Describer
80
+ or optionally use the official LTXV Prompt Enhancer.
81
+ For more details, see the
82
+ About this version
83
+ tab.
84
+ ------------------------------------------------------------------------------------------------------
85
+ For more details see the version description
86
+ Share your results.
87
+
88
+ ## Version Notes (Wan2.2 TI2V 5B 720P)
89
+
90
+ ๐ŸŽฎ
91
+ Live Wallpaper LoRA โ€“ Wan2.2 TI2V 5B Edition
92
+ Live Wallpaper LoRA for Wan2.2 TI2V 5B is a specialized model trained specifically for the unified Text-to-Video and Image-to-Video dense architecture, optimized for superior motion quality and live wallpaper aesthetics.
93
+ ๐Ÿ”ง Training Specs:
94
+ 51 curated video samples at 24fps, 96 frames
95
+ 5,000 steps across 100 epochs with rank 48
96
+ Optimized for Wan2.2's high-compression VAE architecture
97
+ Trained on the efficient 5B dense model (non-MoE)
98
+ Trigger word
99
+ :
100
+ l1v3w4llp4p3r
101
+ ๐ŸŽฏ Motion Excellence:
102
+ Superior movement quality compared to larger model variants
103
+ Enhanced motion fidelity leveraging TI2V 5B's unified framework
104
+ Consumer-GPU friendly with maintained high-quality output
105
+ โšก Performance Advantage:
106
+ Works seamlessly with Wan2.2 TI2V 5B's fast inference
107
+ Compatible with high-compression VAE (64:1 ratio)
108
+ Excellent motion consistency on consumer hardware
109
+ ๐ŸŽฏ
110
+ Perfect for
111
+ : Live wallpaper aesthetics with exceptional movement quality on budget-friendly setups.
112
+ Note
113
+ : Optimized specifically for the 5B dense model - motion quality may vary with MoE variants.
114
+
115
+ ---
116
+
117
+ ## Civitai Links
118
+
119
+ * **[๐Ÿ”— View This Version on Civitai โ†’](https://civitai.com/models/1264662?modelVersionId=2080103)**
120
+ * [View Full Model Page โ†’](https://civitai.com/models/1264662)
121
+ * [View Creator Profile โ†’](https://civitai.com/user/NRDX)
122
+
123
+ ---
124
+
125
+ ## File Information
126
+
127
+ * **Filename**: `livewallpaper_wan22_5b_TI2V_000005000.safetensors`
128
+ * **Size**: 230.70 MB
129
+ * **Hash (AutoV2)**: `F3054548D6`
130
+ * **Hash (SHA256)**: `F3054548D6DBB7EA0084CEF7D3053AA01C410E46D47339F7AFC7F0E2441FC646`