Instructions to use Adorg/mc231104 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adorg/mc231104 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Adorg/mc231104", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Adorg/mc231104", trust_remote_code=True) model = AutoModel.from_pretrained("Adorg/mc231104", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Upload preprocessor_config.json with huggingface_hub
Browse files- preprocessor_config.json +23 -0
preprocessor_config.json
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{
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"crop_pct": 0.875,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"feature_extractor_type": "ConvNextFeatureExtractor",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "ConvNextFeatureExtractor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 384
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}
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}
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