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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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datasets:
- oscar-corpus/OSCAR-2201
- mc4
language:
- he
---
## Hebrew Language Model
State-of-the-art RoBERTa language model for Hebrew.
#### How to use
'''
from transformers import AutoModelForMaskedLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('HeNLP/HeRo')
model = AutoModelForMaskedLM.from_pretrained('HeNLP/HeRo')
''' |