Instructions to use Sami92/XLM-R-Large-Disinfo-Narrative-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sami92/XLM-R-Large-Disinfo-Narrative-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sami92/XLM-R-Large-Disinfo-Narrative-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sami92/XLM-R-Large-Disinfo-Narrative-Classifier") model = AutoModelForSequenceClassification.from_pretrained("Sami92/XLM-R-Large-Disinfo-Narrative-Classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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library_name: transformers
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# Model Card for Model ID
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| **Accuracy** | | | 0.94 | 96 |
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| **Macro avg** | 0.84 | 0.82 | 0.82 | 96 |
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| **Weighted avg** | 0.97 | 0.94 | 0.94 | 96 |
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license: cc-by-4.0
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library_name: transformers
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language:
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- de
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pipeline_tag: text-classification
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---
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# Model Card for Model ID
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| Windräder töten hunderttausende Vögel, verursachen Luftwirbel und Dürre und es werden Wälder für die Windräder gerohdet. | 1.00 | 1.00 | 1.00 | 9 |
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| **Accuracy** | | | 0.94 | 96 |
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| **Macro avg** | 0.84 | 0.82 | 0.82 | 96 |
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| **Weighted avg** | 0.97 | 0.94 | 0.94 | 96 |
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