Instructions to use HeNLP/LongHeRo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HeNLP/LongHeRo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HeNLP/LongHeRo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HeNLP/LongHeRo") model = AutoModelForMaskedLM.from_pretrained("HeNLP/LongHeRo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# HeRO ## Hebrew Language Model State-of-the-art language RoBERTa model for Hebrew. #### How to use ```python from transformers import AutoModelForMaskedLM, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained('HeNLP/HeRo') model = AutoModelForMaskedLM.from_pretrained('HeNLP/HeRo')f3ed02f
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