ml-resources/Kandinsky-S2V-1.0-Lite

image-to-video model by ml-resources

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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. 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 own audio tokens. FramePack memory at three temporal scales carries context from one chunk to the next. Kandinsky-S2V-1.0-Lite-distill — pi-Flow distillation of this checkpoint, 16 steps instead of 50. Text encoders and the VAE are not…

ml-resources/Kandinsky-S2V-1.0-Lite on Hugging Face A short preview, not the full document.

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  1. Kandinsky S2V 1.0 Lite
  2. Examples
  3. Pipeline
  4. Related
  5. Contents
  6. Output
  7. Usage
  8. Performance
  9. Responsible use

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Model overview

ml-resources/Kandinsky-S2V-1.0-Lite 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
2026-11-05T06:42:25.000Z
Last modified
2026-11-05T06:42:26.000Z

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.

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Source: Hugging Face Hub. Metadata observed 2026-11-05T06:53:23.390Z. Daily imports are snapshots, not real-time monitoring.

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