Instructions to use HeTree/HeConEspc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HeTree/HeConEspc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HeTree/HeConEspc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HeTree/HeConEspc") model = AutoModelForSequenceClassification.from_pretrained("HeTree/HeConEspc") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -58,10 +58,12 @@ tokenized_data = raw_dataset_window.map(tokenize_function, batched=True)
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If you use HeConEspc in your research, please cite [HeRo: RoBERTa and Longformer Hebrew Language Models](http://arxiv.org/abs/2304.11077).
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```
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@article{
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title={
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author={Vitaly Shalumov and Harel Haskey},
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year={
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}
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```
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If you use HeConEspc in your research, please cite [HeRo: RoBERTa and Longformer Hebrew Language Models](http://arxiv.org/abs/2304.11077).
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```
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@article{shalumov2024mevaker,
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title={Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language},
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author={Vitaly Shalumov and Harel Haskey and Yuval Solaz},
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year={2024},
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eprint={2403.09719},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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