Instructions to use Sami92/XLM-R-Large-ClaimDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sami92/XLM-R-Large-ClaimDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sami92/XLM-R-Large-ClaimDetection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sami92/XLM-R-Large-ClaimDetection") model = AutoModelForSequenceClassification.from_pretrained("Sami92/XLM-R-Large-ClaimDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 390 Bytes
8222392 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | Telegram Testset
precision recall f1-score support
factual 0.88 0.92 0.90 71
non-factual 0.92 0.88 0.90 78
accuracy 0.90 149
macro avg 0.90 0.90 0.90 149
weighted avg 0.90 0.90 0.90 149
GermEval21 (Facebook Comments)
accuracy = .79
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