Token Classification
Transformers
Safetensors
English
Hebrew
xlm-roberta
code-switching
hebrew
transliteration
romanization
text-to-speech
Eval Results (legacy)
Instructions to use danielrosehill/hebrew-latin-token-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielrosehill/hebrew-latin-token-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="danielrosehill/hebrew-latin-token-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("danielrosehill/hebrew-latin-token-classifier") model = AutoModelForTokenClassification.from_pretrained("danielrosehill/hebrew-latin-token-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Train FacebookAI/xlm-roberta-base on danielrosehill/hebrew-latin-code-switching: test F1 0.941
e6cfd24 verified Download tokenizer.json from danielrosehill/hebrew-latin-token-classifier: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/danielrosehill/hebrew-latin-token-classifier/resolve/main/tokenizer.json
- Command line
-
hf download hf://danielrosehill/hebrew-latin-token-classifier/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/danielrosehill/hebrew-latin-token-classifier/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 4558f350f384fcb92728f0d5032c216dbdf9453bb9cce6f3945db291f358a3cc
- Size of remote file:
- 17.1 MB
- SHA256:
- 3ed3aba76839292e668a3726cf01dfaf90cbc141502955998c4bc233aac28ce6
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