Tasks and inputs
ByteDance/AnimateDiff-Lightning is listed for Text-to-video. It accepts text and produces video. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 7, 2026
Hugging Face repository for Text-to-video.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
ByteDance/AnimateDiff-Lightning is a Hugging Face repository returned by the public Text-to-video task feed. Its recorded download count is 12,850 and it has 993 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.
This record is categorized for Text-to-video. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.
The public repository lists diffusers as its library metadata. Its recorded tags include diffusers, text-to-video, stable-diffusion, animatediff, arxiv:2403.12706, license:creativeml-openrail-m, region:us. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.
Compare prompts at the same duration and resolution. Inspect temporal consistency, physical motion, identity drift and prompt adherence across the whole clip rather than judging a single frame.
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Compare the model on the work you need to complete.
ByteDance/AnimateDiff-Lightning is listed for Text-to-video. It accepts text and produces video. Use the publisher’s input format and preprocessing for your chosen deployment.
Choose duration, resolution and frame rate together. Compare the cost of an accepted clip, including repeat generations.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
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