Token Classification
Transformers
Safetensors
English
Hebrew
xlm-roberta
code-switching
hebrew
transliteration
romanization
text-to-speech
Eval Results (legacy)
Instructions to use Hebrish/Hebrew-Latin-Token-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hebrish/Hebrew-Latin-Token-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Hebrish/Hebrew-Latin-Token-Classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Hebrish/Hebrew-Latin-Token-Classifier") model = AutoModelForTokenClassification.from_pretrained("Hebrish/Hebrew-Latin-Token-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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