Instructions to use mrm8488/bert-mini-5-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-mini-5-finetuned-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/bert-mini-5-finetuned-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-mini-5-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-mini-5-finetuned-squadv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ce08899922017ffd915cd18b50738061ed3688591d35421da42efc667157fde
- Size of remote file:
- 69.7 MB
- SHA256:
- 6fe52b18a8e094abf2c4bad32cc292bd4986bc85d3b95f22d82e3a273f397f3a
路
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