Instructions to use sooks/idbwbase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sooks/idbwbase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sooks/idbwbase") 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("sooks/idbwbase") model = AutoModelForImageClassification.from_pretrained("sooks/idbwbase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa914fb980c35889d39b561a29e4c62571d6f389c1d5303333a00ff9e0f9b780
- Size of remote file:
- 4.86 kB
- SHA256:
- ef635a4a97634b4feedaa4e5cd63c754f17e03e39e81c5a4fd91c3f53428f6ac
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