A beginner's guide to the Wan2.1-With-Lora model by Wan-Video on Replicate

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This is a simplified guide to an AI model called Wan2.1-With-Lora maintained by Wan-Video. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Model overview

wan2.1-with-lora is a video generation model from wan-video that supports LoRA (Low-Rank Adaptation) fine-tuning. The model offers two size options: a 14B parameter version that prioritizes quality, and a 1.3B version optimized for speed. This flexibility makes it suitable for different performance requirements. For faster alternatives with built-in optimizations, consider wan-2.2-t2v-fast or wan-2.2-i2v-fast, which use PrunaAI optimization techniques.

Model inputs and outputs

This model accepts text prompts and optional images to generate video content, with extensive customization parameters for resolution, aspect ratio, and generation quality. The model outputs video files that can be used for content creation, marketing, or creative projects. Key settings allow control over generation speed, prompt adherence, and stylistic variations through LoRA strength parameters.

Inputs

Prompt: Text description of the video you want to generate
Negative Prompt: Things you want to exclude from the video
Image: Optional starting frame for image-to-video generation
Model: Choice between 1.3B (faster) or 14B (higher quality)
Resolution: 480p or 720p (720p not available for 1.3B model)
Aspect Ratio: 16:9, 9:16, or 1:1
Frames: Duration between 1 to 5 seconds (17, 33, 49, 65, or 81 frames)
LoRA URL: Optional URL for a trained LoRA adapter
LoRA Strength Model: Controls the influence of LoRA on the base model (0.0 to 1.0)
LoRA Strength Clip: Controls the influence of LoRA on the CLIP text encoder (0.0 to 1.0)
Fast Mode: Off, Balanced, or Fast acceleration settings
Sample Steps: Number of generation steps (1-60, default 30)
Sample Guide Scale: Controls prompt adherence strength (0-10)
Sample Shift: Adjusts sampling behavior (0-10)
Seed: Optional seed for reproducible results