Instructions to use mrm8488/RuPERTa-base-finetuned-squadv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RuPERTa-base-finetuned-squadv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/RuPERTa-base-finetuned-squadv1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/RuPERTa-base-finetuned-squadv1") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/RuPERTa-base-finetuned-squadv1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5867edd28c25c2ee579c024d8db7cc413a78c1dbd90a644c8a62d5948621e96
- Size of remote file:
- 502 MB
- SHA256:
- f2b5608842802f051e3db73981a11e45926abab99ec1ca96a36ed9c01b7808f3
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