Instructions to use dyyyyyyyy/XTREME_squad_BERT-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dyyyyyyyy/XTREME_squad_BERT-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dyyyyyyyy/XTREME_squad_BERT-base-multilingual-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dyyyyyyyy/XTREME_squad_BERT-base-multilingual-cased") model = AutoModelForMaskedLM.from_pretrained("dyyyyyyyy/XTREME_squad_BERT-base-multilingual-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99d94b7a7a353d4c7c25de8725ff5973e346f4d17ea45b27059aef183a897aa5
- Size of remote file:
- 712 MB
- SHA256:
- 0c315d6a131c2b04f59872621c24c52ed514cc9131579f4bb4d61421e147939c
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