Instructions to use nqvii/fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/fold_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/fold_1") 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_1") model = AutoModelForImageClassification.from_pretrained("nqvii/fold_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2478b45577c4f743facdd06f93e731232ce622a9893451681f3850a66801a543
- Size of remote file:
- 5.2 kB
- SHA256:
- c69c72e64a2cdf076b3440ab51ea3194d77e62689d7e9f6a4e20d3c4dbf795f0
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