Text Classification
Transformers
Safetensors
bert
scibert
data-paper-classification
scholarly-papers
binary-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use zehralx/scibert-data-paper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zehralx/scibert-data-paper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zehralx/scibert-data-paper")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zehralx/scibert-data-paper") model = AutoModelForSequenceClassification.from_pretrained("zehralx/scibert-data-paper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -98,7 +98,7 @@ Concatenated `title + abstract`, truncated to 512 tokens. The model works well w
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```bibtex
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@misc{scibert-data-paper-2026,
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title={SciBERT Data-Paper Classifier},
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author={Zehra Korkusuz},
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year={2026},
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url={https://huggingface.co/zehralx/scibert-data-paper}
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}
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```bibtex
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@misc{scibert-data-paper-2026,
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title={SciBERT Data-Paper Classifier},
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author={Zehra Korkusuz, Kuan-Lin Huang},
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year={2026},
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url={https://huggingface.co/zehralx/scibert-data-paper}
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}
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