ml-resources/Kandinsky-S2V-1.0-Lite-distill
image-to-video model by ml-resources
From the publisher
Model card & documentation
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Speech-to-video generation: an avatar video is produced from a reference frame and a speech track. The whole figure is animated, not only the head. The audio is a condition — the model does not generate sound, it animates the person in the reference frame to match the speech it is given. This is the distilled variant: the sampler is pi-Flow, 16 steps, with classifier-free guidance distilled into the weights, so no negative pass is run at inference. It is roughly 5x faster than the 50-step base model. Each is one reference frame plus one speech track. More examples — other languages, cartoon characters and animals, long videos — are on the project page. Latent diffusion with flow matching. text prompt, and audio-tower features (3584-dim, 25 tokens/s) for the speech. Speech enters through per-layer cross-attention adapters on 13 of the visual blocks, frame-aligned so each latent frame attends only to its…
Read the full model card ↗ · Preview checked 2026-11-05T08:07:27.592Z
Inside the original model card — Document outline
- Kandinsky S2V 1.0 Lite distilled
- Examples
- Pipeline
- Related
- Contents
- Output
- Usage
- Performance
- Responsible use
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Model overview
ml-resources/Kandinsky-S2V-1.0-Lite-distill is a image-to-video model repository published by ml-resources on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-to-video
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- DiffusionTransformer3DS2V
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-11-05T06:42:35.000Z
- Last modified
- 2026-11-05T06:42:36.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-05T06:53:23.390Z. Daily imports are snapshots, not real-time monitoring.
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