Instructions to use nqvii/fold_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/fold_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/fold_5") 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_5") model = AutoModelForImageClassification.from_pretrained("nqvii/fold_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73908e47caa6d38a67fb64892b408d27a4b32ae19c8a18e8b9b074cf7b7de781
- Size of remote file:
- 5.2 kB
- SHA256:
- d95e72a511cf9c09a2c6e136cf6f6b0a26826fd07aa980d3da64f82174297bed
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