NSFW-API/NSFW_Wan_1.3b_motion_helper

NSFW Wan 1.3b Motion Helper LoRA

LoRA Description

The NSFW Wan 1.3b Motion Helper LoRA is a Low-Rank Adaptation specifically designed to significantly enhance video quality, motion consistency, and overall visual style when used with the NSFW Wan 1.3B T2V text-to-video model.

It is particularly optimized for and trained with the wan_1.3B_e10.safetensors checkpoint of the base model.

LoRA Details

• Type: LoRA
• Base Model Compatibility: NSFW Wan 1.3B T2V
• Recommended Base Checkpoint: wan_1.3B_e10.safetensors
• Purpose: To improve video quality, temporal coherence, motion rendering, and stylistic elements in generations from the base NSFW Wan 1.3B T2V model.

Why This LoRA Exists

As detailed in the main NSFW Wan 1.3B T2V model card, the base checkpoint was primarily fine-tuned on images. While capable, this can sometimes lead to:

• Deterioration in video quality.
• Inconsistencies in motion or temporal coherence.
• Less refined stylistic output in video format.

This LoRA was trained specifically to address these limitations, acting as a "motion and quality" enhancement layer on top of the base model's understanding of NSFW content.

How to Use

1. Download the Base Model: Ensure you have the NSFW Wan 1.3B T2V model. The wan_1.3B_e10.safetensors checkpoint is highly recommended for use with this LoRA.
2. Download this LoRA: Get the NSFW_Wan_1.3b_motion_helper.safetensors file.
3. Load in Your Pipeline: In your preferred text-to-video generation environment, load the base model checkpoint (e.g., wan_1.3B_e10.safetensors) and then apply this LoRA.
4. Prompt as Usual: Craft your text prompts as you normally would for the base model. Refer to the prompting-guide.json in the base model repository for guidance.
5. Generate: Enjoy improved video outputs!

Expected Improvements

Using this LoRA with the recommended base checkpoint should result in:

• Smoother and more natural motion.
• Better temporal consistency across frames.
• Enhanced visual fidelity and detail in video sequences.
• Improved overall style and aesthetic coherence for NSFW video content.

Base Model Repository

This LoRA is intended to be used with the main NSFW Wan 1.3B T2V model. You can find the base model, its various epoch checkpoints, and the prompting-guide.json here:

NSFW Wan 1.3B T2V on Hugging Face

Limitations

• This LoRA enhances the output of the base model but is still bound by its inherent capabilities and limitations (e.g., understanding of highly complex or abstract prompts).
• The focus remains on NSFW content; performance on SFW prompts will likely be poor.
• Visual artifacts or inaccuracies may still occur, though they should be reduced compared to using the base model for video without this LoRA.
• All limitations and biases mentioned in the base model card apply.

Ethical Considerations & Responsible AI

This LoRA is an add-on for a model designed to generate NSFW content. All ethical considerations, responsible use guidelines, and limitations outlined in the main NSFW Wan 1.3B T2V model card apply fully when using this LoRA.

• Intended for adult users (18+/21+ depending on local regulations) only.
• Must not be used to create non-consensual depictions of real individuals, to impersonate, defame, harass, or generate content that could cause harm.
• Users are solely responsible for ensuring that their use of this LoRA and the content they generate complies with all applicable laws and regulations.
• Exercise extreme caution and responsibility if distributing content generated.
• The creators do not endorse or condone the creation or distribution of illegal, unethical, or harmful content.

Please refer to the NSFW Wan 1.3B T2V model card for a more comprehensive discussion on ethical considerations.

License

Steal this LoRA!

Disclaimer

The outputs generated using this LoRA in conjunction with the base model are entirely synthetic and computer-generated. They do not depict real people or events unless explicitly prompted to do so with user-provided data. The developers of this LoRA and the base model are not responsible for the outputs created by users.