Instructions to use jnjconsulting/faultclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jnjconsulting/faultclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jnjconsulting/faultclass") 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("jnjconsulting/faultclass") model = AutoModelForImageClassification.from_pretrained("jnjconsulting/faultclass") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 9967afd
Upload preprocessor_config.json
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.33.1"
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}
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.33.1"
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}
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