Instructions to use mrm8488/RuPERTa-base-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RuPERTa-base-finetuned-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/RuPERTa-base-finetuned-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/RuPERTa-base-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/RuPERTa-base-finetuned-squadv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 303cf98ec84947543732bf1c5668c9f997aac1f851ce0796c428139654fec326
- Size of remote file:
- 502 MB
- SHA256:
- 2389a13a8fe2e04d88b36c9ef69e252d2eec425a3368fdb53aa65d4a52f224c4
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