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
Copy of danielrosehill/hebrew-latin-token-classifier @ 01f092f1 (DOI 10.57967/hf/10997; DOI repos cannot be moved)
e303bc1 verified Download training_args.bin from Hebrish/Hebrew-Latin-Token-Classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/Hebrish/Hebrew-Latin-Token-Classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://Hebrish/Hebrew-Latin-Token-Classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Hebrish/Hebrew-Latin-Token-Classifier/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 23b5e54796e73790c6d720baa52bc394b0432f48228e1668711b41b39d77ca02
- Size of remote file:
- 5.84 kB
- SHA256:
- cdf1174c9c88da6806fafe786085004630742fc0cbc73c83975506c7cb0624ff
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