Instructions to use HorcruxNo13/cvt-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/cvt-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/cvt-13") 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("HorcruxNo13/cvt-13") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/cvt-13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 879b30ef171e78f14ff6cca3a74fabc04420ac5b2670b99806ff06d051d9108b
- Size of remote file:
- 4.03 kB
- SHA256:
- c11a87f19148ad180e0ee5b5c8de778d5b2165e7a62f09bc93ddd67f834c797f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.