Run a Stable Diffusion Text to Video Job
Based on ComfyUI, the SDV Pipeline modules for Lilypad allow you generate videos from text prompts on Lilypad using Stable Diffusion Video and related models.
The SDV Pipeline modules are designed to take your text prompt, generate a still frame using SDXL, then use that as the input to the SDV model, producing an APNG (animated PNG), WebP video, and an MP4 video all in one go.
Before running sdv, make sure you have the Lilypad CLI installed on your machine and your private key environment variable is set. This is necessary for operations within the Lilypad network.
To run SDV v1.0 or 1.1 Pipeline in Lilypad, you can use the following commands:
To view the results in a local directory, navigate to the local folder.
To view the results on IPFS, navigate to the IPFS CID result output.
Please be patient! IPFS can take some time to propagate and doesn't always work immediately.
As Lilypad modules are currently deterministic, running this command with the same text prompt will produce the same image, since the same seed is also used (the default seed is 0).
If you wish to specify more than one tunable, such as the number of steps, simply add more -i flags. For example, to change or improve the quality of the image generated add "Steps=x" with x = (min: 5. Max: 200):
See the options and tunables section for more information on what tunables are available.
See this beginner-friendly article on how seeds work for more info on this
The following tunables are available. All of them are optional, and have default settings that will be used if you do not provide them.
Prompt
A text prompt for the model
"question mark floating in space"
Any string
Framerate
The framerate of the video
8
Any valid positive integer between 1 and 20
Seed
A seed for the image model
42
Any valid non-negative integer
Steps
The number of steps to run the model for
50
Any valid non-negative integer from 5 to 200 inclusive
Scheduler
The scheduler to use for the model
normal
normal, karras, exponential, sgm_uniform, simple, ddim_uniform
Sampler
The sampler to use for the model
euler_ancestral
"euler", "euler_ancestral", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm"
Batching
How many images to produce
1
1, 2, 4, 8
VideoSeed
A seed for the video model
42
Any valid non-negative integer
VideoSteps
The number of steps to run the video model for
50
Any valid non-negative integer from 5 to 70 inclusive
VideoScheduler
The scheduler to use for the video model
normal
normal, karras, exponential, sgm_uniform, simple, ddim_uniform
VideoSampler
The sampler to use for the video model
euler_ancestral
"euler", "euler_ancestral", "heun", "heunpp2", "dpm_2", "dpm_2_ancestral", "lms", "dpm_fast", "dpm_adaptive", "dpmpp_2s_ancestral", "dpmpp_sde", "dpmpp_sde_gpu", "dpmpp_2m", "dpmpp_2m_sde", "dpmpp_2m_sde_gpu", "dpmpp_3m_sde", "dpmpp_3m_sde_gpu", "ddpm", "lcm"
Learn more about this Lilypad module on Github.
