Instructions to use nvidia/mit-b4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b4") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("nvidia/mit-b4") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b4", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md
3844dda -
Update license
c41fa25
-
Add TF weights (#1)
- Add TF weights (4e9bdb66da0984cee0b0b94c91103db5b8aa7555)c6b324b
-
Remove reshape_last_stage
4c667d1
-
Update README.md
366fbee -
Create README.md
2f7bd67
-
Update preprocessor_config.json
71e812d
-
Set do_pad to False
c92426d
-
First commit
2422989 -
initial commit
a1ce0ad