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:
- 1743690ed5cb421e8df3fb38dff5f2bd84556225aeb6b12ff5b3514d211199ea
- Size of remote file:
- 436 MB
- SHA256:
- 9b442a079d88b5c02cea285bc50469d13bfdb1d0cfa39a7e33c1301ee8319357
路
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