Question Answering
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
bert
Eval Results (legacy)
Instructions to use deepset/bert-large-uncased-whole-word-masking-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/bert-large-uncased-whole-word-masking-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/bert-large-uncased-whole-word-masking-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/bert-large-uncased-whole-word-masking-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/bert-large-uncased-whole-word-masking-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit 路
8ebfa4a
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Parent(s): bb1f092
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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