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Fix usage instructions: correct model class / plugin guidance, English-only

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  1. README.md +22 -14
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@@ -7,27 +7,35 @@ tags:
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  - camera-movement
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  - video-understanding
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  - qwen3-vl
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- - sft
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  - distillation
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  ---
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  # CamDistill-4B
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- Camera-movement 蒸馏 SFT 微调模型,基于 `Qwen/Qwen3-VL-4B-Instruct`。
 
 
 
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- - Checkpoint: `checkpoint-1326`
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- - 训练框架: [ms-swift](https://github.com/modelscope/ms-swift)
 
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- ## 使用
 
 
 
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- ```python
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- from transformers import AutoModelForCausalLM, AutoProcessor
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- model = AutoModelForCausalLM.from_pretrained("ddz16/CamDistill-4B", torch_dtype="bfloat16", device_map="auto")
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- processor = AutoProcessor.from_pretrained("ddz16/CamDistill-4B")
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- ```
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- ## Links
 
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- - **Paper**: [Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation](https://huggingface.co/papers/2608.10932)
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- - **Project page**: [https://ddz16.github.io/cammotion.github.io](https://ddz16.github.io/cammotion.github.io)
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- - **GitHub**: [https://github.com/ddz16/CamDistill](https://github.com/ddz16/CamDistill)
 
 
 
 
 
 
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  - camera-movement
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  - video-understanding
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  - qwen3-vl
 
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  - distillation
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  ---
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  # CamDistill-4B
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+ Camera-movement understanding model trained with **Camera Token Distillation** on top of
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+ `Qwen/Qwen3-VL-4B-Instruct`. A lightweight Camera Token Module learns geometry-aware camera
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+ tokens (distilled from VGGT) and injects them into the language model. Given a video, it outputs
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+ structured JSON describing every camera-movement segment.
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+ - **Paper**: [Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation](https://huggingface.co/papers/2608.10932)
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+ - **Project page**: https://ddz16.github.io/cammotion.github.io
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+ - **Code**: https://github.com/ddz16/CamDistill
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+ > ⚠️ **This model cannot be loaded with plain 🤗 Transformers.** It contains an extra Camera Token
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+ > Module and a patched forward pass. Loading it as a standard `Qwen3VLForConditionalGeneration`
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+ > would silently drop those weights and produce incorrect results. Use the CamDistill repo, which
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+ > registers the required custom model type through a plugin.
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+ ## Usage
 
 
 
 
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+ Clone the [CamDistill repo](https://github.com/ddz16/CamDistill), then run (camera tokens are generated internally — **no online
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+ VGGT required**):
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+ ```bash
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+ python camera_movement_sft/infer_single.py \
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+ --model ddz16/CamDistill-4B \
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+ --video /path/to/video.mp4 \
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+ --variant camdistill
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+ ```
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+
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+ See the repo's README for environment setup and batch evaluation.