Instructions to use OpenGVLab/InternViT-300M-448px with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternViT-300M-448px with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="OpenGVLab/InternViT-300M-448px", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/InternViT-300M-448px", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8befd9d6dd7c4872f70fe85b8ef8775c8cc96b9c3dd71881b62e955eaca2794
- Size of remote file:
- 44.1 MB
- SHA256:
- aa10b9445df664dbba8feab0c25f3706d2229b466b390a4e1bb4c603a9a6da8a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.