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README.md

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+---
+license: apache-2.0
+base_model: Wan-AI/Wan2.2-S2V-14B
+pipeline_tag: image-to-video
+---
+
+# Wan2.2-S2V-14B (Diffusers layout)
+
+This is [Wan-AI/Wan2.2-S2V-14B](https://huggingface.co/Wan-AI/Wan2.2-S2V-14B)
+— a model that animates a picture of a person in sync with a voice recording —
+repacked into the folder layout that
+[FastVideo](https://github.com/hao-ai-lab/FastVideo) loads.
+
+**No weights were changed.** The video model tensors are byte-identical copies
+of the official release. The text encoder, VAE, tokenizer and scheduler come
+from Wan-AI's own Diffusers release of Wan2.1 (the same weights S2V uses), and
+the wav2vec2 speech encoder is the one bundled inside the official S2V repo.
+
+Made with
+[`scripts/checkpoint_conversion/wan_s2v_to_diffusers.py`](https://github.com/hao-ai-lab/FastVideo/pull/1683)
+from FastVideo PR #1683.
+
+## Verification status
+
+- Checked: all 1260 video-model tensors load into FastVideo's model with the
+  correct names and shapes (the conversion script verifies this automatically
+  and refuses to produce output otherwise).
+- Not yet checked: end-to-end video generation on a GPU. If you run it and
+  find problems, please comment on the PR above.
+
+## Usage (with FastVideo, once PR #1683 is merged)
+
+```python
+from fastvideo import VideoGenerator
+
+gen = VideoGenerator.from_pretrained("SuhaanCoding/Wan2.2-S2V-14B-Diffusers")
+gen.generate_video(
+    prompt="...",
+    image_path="face.jpg",
+    audio_path="speech.wav",
+    output_path="out.mp4",
+    save_video=True,
+)
+```