Instructions to use James332/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use James332/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="James332/cppe5_use_data_finetuning")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("James332/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("James332/cppe5_use_data_finetuning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0110d2b3fa0160663be074dec21b7774c01827a1e80554ab26c843f9df37269e
- Size of remote file:
- 166 MB
- SHA256:
- 11253fe3e746372edf07f26e614bb2f021215a1a1d2c9dd9fc2100da0c01cc8b
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