Video-Text-to-Text
Transformers
Safetensors
qwen3_vl
image-text-to-text
camera-movement
video-understanding
qwen3-vl
vggt-injection
Instructions to use ddz16/CamInject-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ddz16/CamInject-4B with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ddz16/CamInject-4B") model = AutoModelForMultimodalLM.from_pretrained("ddz16/CamInject-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| base_model: Qwen/Qwen3-VL-4B-Instruct | |
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: video-text-to-text | |
| tags: | |
| - camera-movement | |
| - video-understanding | |
| - qwen3-vl | |
| - sft | |
| - vggt-injection | |
| # CamInject-4B | |
| This repository contains the **CamInject-4B** model from the paper [Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation](https://huggingface.co/papers/2608.10932). | |
| **Project page**: https://ddz16.github.io/cammotion.github.io | |
| **GitHub**: https://github.com/ddz16/CamDistill | |
| Camera-movement VGGT-Direct 注入 SFT 微调模型,基于 `Qwen/Qwen3-VL-4B-Instruct`。 | |
| - Checkpoint: `checkpoint-1326` | |
| - 训练框架: [ms-swift](https://github.com/modelscope/ms-swift) | |
| ## 使用 | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoProcessor | |
| model = AutoModelForCausalLM.from_pretrained("ddz16/CamInject-4B", torch_dtype="bfloat16", device_map="auto") | |
| processor = AutoProcessor.from_pretrained("ddz16/CamInject-4B") | |
| ``` |