Instructions to use mrm8488/bert-small-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-small-finetuned-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/bert-small-finetuned-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-small-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-small-finetuned-squadv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a110ff0793656924c9e874205371a789ce718e287bd25fbb3de9602654d457a
- Size of remote file:
- 1.49 kB
- SHA256:
- 7a44d4ee7c3bc6aa369351383c9851fcdcc9729f0241e22e80e1fea47715f522
路
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