Instructions to use nqvii/fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/fold_2") 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("nqvii/fold_2") model = AutoModelForImageClassification.from_pretrained("nqvii/fold_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9b4bb7c9ba0c12b96de40efa68783311de89142bf1cc44f8ef7c2208e96c6c7
- Size of remote file:
- 5.2 kB
- SHA256:
- 1b95f7ecffce4683a6f9b05863aa3c061c49a85e55035c2c84dda93f6cf6fb68
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