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:
- 787ae1f74f00d150aefb0123d279ed754d74fb8da38454c7961cb320c7d85247
- Size of remote file:
- 436 MB
- SHA256:
- dbcb656f5e6e0b0bf0eaf0a8e548ee78bff9cf3c24b5d00aa9839d731ef00d54
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