Instructions to use xiaomoguhzz/VisionEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xiaomoguhzz/VisionEncoder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("xiaomoguhzz/VisionEncoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9f33b2519200639ffae4b223e961348d8f4376557aa8f1c3886cce019af21c3
- Size of remote file:
- 857 MB
- SHA256:
- 3967ea19856093beecc453f6b9e74658e4597247abb9f139fa27bf7ca18c8bc8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.