Instructions to use metythorn/khmer-xlm-roberta-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use metythorn/khmer-xlm-roberta-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="metythorn/khmer-xlm-roberta-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("metythorn/khmer-xlm-roberta-small") model = AutoModelForMaskedLM.from_pretrained("metythorn/khmer-xlm-roberta-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b086c80027e0953694765a709013669a0461ee7bc3f2dc54adef8fa6a2f62ae3
- Size of remote file:
- 375 MB
- SHA256:
- 5e0c1d47248bff69b09cd74f577a7db66f07827ab7ac8efb2162576f60481b70
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