Any-to-Any
Transformers
Safetensors
qwen3_5
image-text-to-text
video-editing
agent
tool-use
long-horizon
reinforcement-learning
qwen3.5
Instructions to use tencent/WeVisCut with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/WeVisCut with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("tencent/WeVisCut") model = AutoModelForMultimodalLM.from_pretrained("tencent/WeVisCut", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/wevisioncut_logo.png from tencent/WeVisCut: direct link, hf CLI and curl.
- Browser
- Download file 515 kB
-
https://huggingface.co/tencent/WeVisCut/resolve/main/assets/wevisioncut_logo.png
- Command line
-
hf download hf://tencent/WeVisCut/assets/wevisioncut_logo.png
-
curl -L -o wevisioncut_logo.png https://huggingface.co/tencent/WeVisCut/resolve/main/assets/wevisioncut_logo.png
515 kB

- Xet hash:
- 9e509add12435fa84d0f30b60f08d9aef20600589f23a728cb4323c42c533b83
- Size of remote file:
- 515 kB
- SHA256:
- ee4db089533179078a21fcabbbd8d696b5133bdd69152ab7853d15a0fe36b1f2
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