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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a85d4c49e975be3fba0c5f60b454897b77ab2035dc807430a6a37b7fcaabf62
- Size of remote file:
- 438 MB
- SHA256:
- 997a8012a07cef470869a18bce1540cf179b41dd7cfdf8256a982c30da04bfeb
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