Instructions to use Garkpit/test_one with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Garkpit/test_one with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Garkpit/test_one") 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("Garkpit/test_one") model = AutoModelForImageClassification.from_pretrained("Garkpit/test_one") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb1b6c2fcffdd0f1a7777a23729ca51583384d147ecbaff3833136bdf5d5f762
- Size of remote file:
- 343 MB
- SHA256:
- 6896a22ec883dded555d714e2edb8306339d7580f4428b11d3f56c69b0ae17e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.