Instructions to use GKLMIP/electra-myanmar-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GKLMIP/electra-myanmar-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GKLMIP/electra-myanmar-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GKLMIP/electra-myanmar-base-uncased") model = AutoModelForMaskedLM.from_pretrained("GKLMIP/electra-myanmar-base-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f12702becafaa4dab4d591151c1a318495723b1d868a932f178a543d4e574b73
- Size of remote file:
- 421 MB
- SHA256:
- 9288650ca1082feb49d28b3f29e051536739ce1495acbd6d9093cdf2e4b813e5
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