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Wan2.1 parameter sweep

We’ve been playing with Alibaba’s WAN2.1 text-to-video model lately. Like most image and video generation models, Wan has a lot of input parameters, and each of them can have a profound impact on the quality of the generated output. What happens when you tweak those mysterious inputs? Let’s find out. The experiment We wanted to see how the guidance scale and shift input parameters affect the output. For our experiment, we used the WAN2.1 14b text-to-video model with 720p resolution. To do this, we did what’s called a “parameter sweep”, systematically testing different combinations of input values to understand how they affect the output. We generated videos for each combination of guidance scale and shift values, keeping all other parameters constant. We kept the following inputs consistent across all the videos: prompt : "A smiling woman walking in London at night" seed : 42 frames : 81 sample_steps : 30 We then varied just these two inputs, testing against a range of values: sample_guide_scale : from 0 to 10 sample_shift : from 1 to 9 …

Announced

05 Mar 2025 00:00 UTC