Question Answering
Transformers
PyTorch
JAX
Safetensors
English
bert
bert-base
Eval Results (legacy)
Instructions to use csarron/bert-base-uncased-squad-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csarron/bert-base-uncased-squad-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="csarron/bert-base-uncased-squad-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("csarron/bert-base-uncased-squad-v1") model = AutoModelForQuestionAnswering.from_pretrained("csarron/bert-base-uncased-squad-v1") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fafdc56565a445a8cd17f6865fd14c78ba11e3bf8772ad2b54383dd708646b47
- Size of remote file:
- 438 MB
- SHA256:
- 53317378053dac783e2aa032302f435b2937515f2abe9048dfa088c08affcfbe
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