Instructions to use nvidia/mit-b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b0") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("nvidia/mit-b0") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b0") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a25fcdc3946535077ab7e8df5c8e39d3a071848ee9657b435490daa2f582e32
- Size of remote file:
- 14.6 MB
- SHA256:
- 37aff8e82e97eb72227f2b693f19885c5bcfef66f8667eeed529cff9fa67ef5d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.