Text Classification
Transformers
Safetensors
English
xlm-roberta
skill-detection
sentence-classification
ESCO
text-embeddings-inference
Instructions to use nurlanm/ESCOXLM-R_ENG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nurlanm/ESCOXLM-R_ENG with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nurlanm/ESCOXLM-R_ENG")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nurlanm/ESCOXLM-R_ENG") model = AutoModelForSequenceClassification.from_pretrained("nurlanm/ESCOXLM-R_ENG") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -26,5 +26,5 @@ Musazade, N., Zhang, M., & Mezei, J. (2025, August). Cross-Lingual Sentence-Leve
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booktitle={Proceedings of the 8th International Conference on Natural Language and Speech Processing (ICNLSP-2025)},
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pages={410--415},
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year={2025},
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url={https://aclanthology.org/2025.icnlsp-1.40
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}
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booktitle={Proceedings of the 8th International Conference on Natural Language and Speech Processing (ICNLSP-2025)},
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pages={410--415},
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year={2025},
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url={https://aclanthology.org/2025.icnlsp-1.40.pdf}
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}
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