Instructions to use h3110Fr13nd/guj-eng-code-switch-indic-bert-data2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h3110Fr13nd/guj-eng-code-switch-indic-bert-data2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="h3110Fr13nd/guj-eng-code-switch-indic-bert-data2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("h3110Fr13nd/guj-eng-code-switch-indic-bert-data2") model = AutoModelForTokenClassification.from_pretrained("h3110Fr13nd/guj-eng-code-switch-indic-bert-data2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- feea08510a145b9ec399e12b85b15362c0fcb48dce3f1b9156531390768dcd0f
- Size of remote file:
- 15.3 MB
- SHA256:
- d5a55f5fc027091bb4fb4175e2392cba33e7c1480ab7cdebf2fc902dfa4da292
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