Instructions to use GKLMIP/electra-khmer-small-uncased-tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GKLMIP/electra-khmer-small-uncased-tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GKLMIP/electra-khmer-small-uncased-tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GKLMIP/electra-khmer-small-uncased-tokenized") model = AutoModelForMaskedLM.from_pretrained("GKLMIP/electra-khmer-small-uncased-tokenized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d56f3038d99fbc58fca30849530c7ee54acdf45a7744842eb435726cdf1fdb4
- Size of remote file:
- 154 MB
- SHA256:
- 144adebca9dd0bd290ea40ed1b495da5027a301f9a003d98ac5275740b0c8529
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