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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:38ccfdde51b65de42d681fb44f2d523f296dde5ba86f4ca3bac68067a2164cff
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size 434095120
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