Instructions to use VMware/bert-base-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/bert-base-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/bert-base-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/bert-base-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/bert-base-mrqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4d3d549c036365d19e474c2c2a0426dff1ad3b50dd4aee5101930f9f0b900c9
- Size of remote file:
- 436 MB
- SHA256:
- b345deb71a698345a022cb5931dbd60167aa521c461394e0c72fac7f0449e757
路
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