Instructions to use orisuchy/Descriptive_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orisuchy/Descriptive_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="orisuchy/Descriptive_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("orisuchy/Descriptive_Classifier") model = AutoModelForSequenceClassification.from_pretrained("orisuchy/Descriptive_Classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -25,8 +25,8 @@ print(outputs)
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"""
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Output:
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[[
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{'label': 'Descriptive', 'score': 0.
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{'label': 'Not Descriptive', 'score': 0.
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"""
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```
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#### Or, if you want only the final class:
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"""
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Output:
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[[
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{'label': 'Descriptive', 'score': 0.999764621257782},
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{'label': 'Not Descriptive', 'score': 0.00023541577684227377}]]
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"""
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```
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#### Or, if you want only the final class:
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