Instructions to use VMware/bert-large-mrqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VMware/bert-large-mrqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VMware/bert-large-mrqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("VMware/bert-large-mrqa") model = AutoModelForQuestionAnswering.from_pretrained("VMware/bert-large-mrqa") - Notebooks
- Google Colab
- Kaggle
Commit 路
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Parent(s): c13ba56
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (3d8fa2c503d417a290ca0c7ef0c723f4f847b8d3)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:34a3a2a169d7df33940698aeaf11e3ebf2ab23a4b529756ba5426941e86e71dc
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size 1336428352
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