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:
- 599a1570f3fd4a3f4ab163b42fad99975402b2426bdfb378e50b346fae67761c
- Size of remote file:
- 375 MB
- SHA256:
- 4107873cb1e5995c0e72293113f83605ef13b5395bd880c23f977de6e7c54399
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