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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/RuPERTa-base-finetuned-squadv2")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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upload flax model
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allow flax
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Migrate model card from transformers-repo
Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/mrm8488/RuPERTa-base-finetuned-squadv2/README.md4b3c00a
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