Instructions to use nqvii/fold_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqvii/fold_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nqvii/fold_3") 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_3") model = AutoModelForImageClassification.from_pretrained("nqvii/fold_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2910fa15afeb1d6a34615b202b48a8d0cb2670f3708a7dad96d5742a339899f
- Size of remote file:
- 5.2 kB
- SHA256:
- e2b615c29545b5bafa7084697f3ba4303cc0e0232660149693606ff75fee27b1
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