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:
- f94cdcb0c4c4aaa01b8732358aad16ceaef7c29a31d82466901e3ae86f2a0925
- Size of remote file:
- 80.3 MB
- SHA256:
- 90d7e6b4c665c5b934ce55894fd856fc5dab9e2c93cca79361d5dcb65bbc117f
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