Instructions to use Fu-chiang/bit-50-Otisis-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fu-chiang/bit-50-Otisis-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Fu-chiang/bit-50-Otisis-binary") 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("Fu-chiang/bit-50-Otisis-binary") model = AutoModelForImageClassification.from_pretrained("Fu-chiang/bit-50-Otisis-binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7fe1ee4c6c7538bbbf1699a70995820c61c27595d8a53659bed563cfd69280e2
- Size of remote file:
- 188 MB
- SHA256:
- d2efc9aab2d9259e66e7d21e130f5394e2ba8c4b0ccec1dd4f5f0dc62fee4517
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