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:
- 321e3f076adb9f84933e8e4666b6f2c4e860d131d4d7445ab9e3e124923c2afe
- Size of remote file:
- 438 MB
- SHA256:
- e11c78b01522080b9507d24e3bbaa96c6b61a3e91b8c1a71a5e5deb598f12afb
路
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