Instructions to use Nursultan03/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nursultan03/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Nursultan03/model") 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("Nursultan03/model") model = AutoModelForImageClassification.from_pretrained("Nursultan03/model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 794eba4d806cb4b94a964b205ec08c7268d93193e89ab69504a158d2d0e2d441
- Size of remote file:
- 44.8 MB
- SHA256:
- 7501277d1aa909bd37944ea2e3ebd5281115750b6500ceb77c6e2e35cf741fa3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.