Instructions to use roshnir/mBert-finetuned-mlqa-dev-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshnir/mBert-finetuned-mlqa-dev-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="roshnir/mBert-finetuned-mlqa-dev-hi")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("roshnir/mBert-finetuned-mlqa-dev-hi") model = AutoModelForQuestionAnswering.from_pretrained("roshnir/mBert-finetuned-mlqa-dev-hi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 877c1d6214ac94a5275857e2eeb5302d0309b0ef59bca9c90c03c7f5673f806c
- Size of remote file:
- 667 MB
- SHA256:
- bb9f0adfb8422380127b67f0cbdf3ef98925f6c9557d8435fb5010ab7cc9c6fc
路
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