Instructions to use GKLMIP/electra-khmer-base-uncased-tokenized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GKLMIP/electra-khmer-base-uncased-tokenized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="GKLMIP/electra-khmer-base-uncased-tokenized")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("GKLMIP/electra-khmer-base-uncased-tokenized") model = AutoModelForMaskedLM.from_pretrained("GKLMIP/electra-khmer-base-uncased-tokenized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4146183ed3c3b7321361ea509bfdcd0754ad0421ad86a4d6f91f832b09d092d5
- Size of remote file:
- 443 MB
- SHA256:
- 63fa7bbb1100eed547dc32589f9c44714b9e96e549094958dcf1c3716744914a
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