Instructions to use vnktrmnb/MBERT_FT-TyDiQA_S47 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vnktrmnb/MBERT_FT-TyDiQA_S47 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="vnktrmnb/MBERT_FT-TyDiQA_S47")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("vnktrmnb/MBERT_FT-TyDiQA_S47") model = AutoModelForQuestionAnswering.from_pretrained("vnktrmnb/MBERT_FT-TyDiQA_S47", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e8f4f4b1ff6bd3ca7622466fbc118bfc08241cc9c77e64d6615029a2a703c4b
- Size of remote file:
- 709 MB
- SHA256:
- c2e0a80b5b9175e5d515e03e69626ec4f13f9ce619156936754d615b39ee912c
路
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