Instructions to use roshnir/bert-base-multi-mlqa-dev-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshnir/bert-base-multi-mlqa-dev-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="roshnir/bert-base-multi-mlqa-dev-en")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("roshnir/bert-base-multi-mlqa-dev-en") model = AutoModelForQuestionAnswering.from_pretrained("roshnir/bert-base-multi-mlqa-dev-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a4ac60b861650e4ec61eec4a6046372699a701e7abb76f9f08cc13ec9f43e92
- Size of remote file:
- 667 MB
- SHA256:
- f89ee3dd9af0802d8c9c6289e540929380ac89d654bcfb530ac8929c59a4f910
路
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