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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d258e50de3105047f8bdc37802db3a58c1a3a2b7d1ccd86a0fbc3b5a81c9046
- Size of remote file:
- 1.46 kB
- SHA256:
- 50e6d4fbb7481ec1bfc739f8b97628f4600cc80a60da514e7f10630ceba80944
路
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