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GSsmart/Wan2.2_GSsmart_Uncensored

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  • classification m-uncensored
  • files 4
  • author_summary 1 models
  • readme_text full
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
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created 2026-10-04

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Metadata

License
apache-2.0
Tags
wan2.2 wan GSsmart T2V I2V lora comfyui video uncensored image-text-to-video base_model:Wan-AI/Wan2.2-I2V-A14B base_model:adapter:Wan-AI/Wan2.2-I2V-A14B

Related

Total size
2.32 GB
Files
4
Quantizations
1
Registered
2026-10-04 14:58
Last updated on HF
2026-10-04 14:30

Files by quantization

Auxiliary files 4 files 2.32 GB
Wan2.2_LightX2V_high_n54vv.safetensors 1.16 GB 13be3b91 download
Wan2.2_LightX2V_low_n54vv.safetensors 1.16 GB 85fb420f download
README.md 3.67 KB 9bdaa7a2 download
.gitattributes 2.67 KB 57f07a90 download

README current version from Hugging Face


tags:

  • wan
  • wan2.2
  • GSsmart
  • T2V
  • I2V
  • lora
  • comfyui
  • video
  • uncensored
    base_model: Wan-AI/Wan2.2-I2V-A14B
    instance_prompt: null
    license: apache-2.0
    pipeline_tag: image-text-to-video

Wan2.2 GSsmart Uncensored

Left: I2V | Right: T2V

Model description

I got tired of switching back and forth between I2V and T2V models, and swapping LightX2V (or other LoRAs) suited to each. When you mostly generate videos for testing or “what if” runs, that repetitive setup gets old fast.

These LightX2V LoRAs are meant for both I2V and T2V, and they are uncensored. If you’re in the same boat, they might save you some workflow friction.


What to expect

  • Tuned to understand mechanics and motion from explicit prompts.
  • Female / male body accuracy is roughly 80–85% on T2V.
  • On I2V, results depend heavily on the input image. Bringing a male or female into the scene (a man || woman appears) depends a lot on how clear and explicit your prompt is, be descriptive about clothing, body.

Stacking other LoRAs

Other well-trained LoRAs usually work fine at about 0.55–0.65 strength on top of this pair.

Downside: if you lower this LoRA’s strength, you are also weakening the LightX2V / speed behavior. Without another LightX2V pair to compensate, output can get blurry with broken motion. Keep this pair at full (or near-full) strength unless you add a separate speed LoRA.


Files

File Stage
Wan2.2_LightX2V_high_n54vv.safetensors High noise
Wan2.2_LightX2V_low_n54vv.safetensors Low noise

Appearance-Only Enhancers

The appearance side of the LoRA is intentionally tuned down for better stacking with other LoRAs.
Rarely needed in I2V scenes, but for T2V these appearance-only LoRAs can enhance and compensate for the tuned-down appearances.

File Variant Strength
male_genitalia_enhancer_high.safetensors High noise 0.55
male_genitalia_enhancer_low.safetensors Low noise 0.55
female_genitalia_enhancer_high.safetensors High noise 0.5
female_genitalia_enhancer_low.safetensors Low noise 0.5

🙏 Acknowledgements

LightX2V | Wan-AI

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