Instructions to use sungile/custom-object-test7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sungile/custom-object-test7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="sungile/custom-object-test7")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("sungile/custom-object-test7") model = SegformerForSemanticSegmentation.from_pretrained("sungile/custom-object-test7") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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{
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"do_normalize": true,
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"do_reduce_labels":
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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{
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"do_normalize": true,
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"do_reduce_labels": false,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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