Instructions to use Addaci/bert-base-multilingual-cased-finetuned-yiddish-experiment-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Addaci/bert-base-multilingual-cased-finetuned-yiddish-experiment-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Addaci/bert-base-multilingual-cased-finetuned-yiddish-experiment-3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Addaci/bert-base-multilingual-cased-finetuned-yiddish-experiment-3") model = AutoModelForMaskedLM.from_pretrained("Addaci/bert-base-multilingual-cased-finetuned-yiddish-experiment-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b629ec955841a68ec41cd1a751a21d376b654d0ee068087304ef8189903d704c
- Size of remote file:
- 5.5 kB
- SHA256:
- 25eb4a2e10ec0d433a2c1cbe100f4b7b8ddffbf0b7f7be8cb0de207e1d689716
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