Instructions to use GKLMIP/bert-khmer-base-uncased-tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GKLMIP/bert-khmer-base-uncased-tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GKLMIP/bert-khmer-base-uncased-tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GKLMIP/bert-khmer-base-uncased-tokenized") model = AutoModelForMaskedLM.from_pretrained("GKLMIP/bert-khmer-base-uncased-tokenized") - Notebooks
- Google Colab
- Kaggle
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README.md
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https://github.com/GKLMIP/Pretrained-Models-For-Khmer
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If you use our model, please consider citing our paper:
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```
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@article{,
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https://github.com/GKLMIP/Pretrained-Models-For-Khmer
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If you use our model, please consider citing our paper:
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```
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@article{,
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