Instructions to use dwmit/transliterate_try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dwmit/transliterate_try with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dwmit/transliterate_try")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dwmit/transliterate_try") model = AutoModelForTokenClassification.from_pretrained("dwmit/transliterate_try", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd14f7c9ec08a5fff0e1534d607df1bfd56a01926051b2d38976de1eb4d89fe2
- Size of remote file:
- 3.71 kB
- SHA256:
- b638173aaeea390c50a496bd3d90acded47047e2114c5b8a9193b2d6d7a680b6
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