Instructions to use mrm8488/bert-tiny-4-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-tiny-4-finetuned-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/bert-tiny-4-finetuned-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-tiny-4-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-tiny-4-finetuned-squadv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c63556fdebdf8681ecad49a4bdba384d5d52987b9d1d3b21e503385fa4263bf2
- Size of remote file:
- 23.8 MB
- SHA256:
- 5ec2d5788e4606844f6c0b5be230d675dc59a668d7048edd8a8d8cddfb3f9e73
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