Instructions to use twmkn9/bert-base-uncased-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twmkn9/bert-base-uncased-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="twmkn9/bert-base-uncased-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("twmkn9/bert-base-uncased-squad2") model = AutoModelForQuestionAnswering.from_pretrained("twmkn9/bert-base-uncased-squad2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffe207446a97480bd102b608fe39e4d275535cd522fd5648181d42130c27cf17
- Size of remote file:
- 436 MB
- SHA256:
- 96c0c2948a642789fbf4dc10095b059dc34e45e07bf6722e0d81ce4c9afc9479
路
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