Instructions to use HeNLP/HeRo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HeNLP/HeRo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HeNLP/HeRo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HeNLP/HeRo") model = AutoModelForMaskedLM.from_pretrained("HeNLP/HeRo") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -28,6 +28,6 @@ If you use HeRo in your research, please cite [HeRo: RoBERTa and Longformer Hebr
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title={HeRo: RoBERTa and Longformer Hebrew Language Models},
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author={Vitaly Shalumov and Harel Haskey},
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year={2023},
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journal={2304.11077},
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}
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```
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title={HeRo: RoBERTa and Longformer Hebrew Language Models},
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author={Vitaly Shalumov and Harel Haskey},
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year={2023},
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journal={arXiv:2304.11077},
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}
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```
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