Instructions to use ania3000/kubert-from_multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ania3000/kubert-from_multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ania3000/kubert-from_multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ania3000/kubert-from_multilingual") model = AutoModelForMaskedLM.from_pretrained("ania3000/kubert-from_multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa58ef509840781db3531918621b1c033cb2fc9a3a03c98d2ee3c0611cf8cdd1
- Size of remote file:
- 5.84 kB
- SHA256:
- 548b435c6ec58c0b70e6942f7b7bc012d97a002e2cdedc4b76172712e831f4ce
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