Instructions to use Mathnub/rubert-base-sberquad_ai-f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathnub/rubert-base-sberquad_ai-f with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Mathnub/rubert-base-sberquad_ai-f")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Mathnub/rubert-base-sberquad_ai-f") model = AutoModelForQuestionAnswering.from_pretrained("Mathnub/rubert-base-sberquad_ai-f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ffcc3a53a28a36903062e4c9ab401bc2fdedd658c02c78e6dbf970cd69040a8
- Size of remote file:
- 711 MB
- SHA256:
- 3a504d0b5101bd836892b73fa73d4a294f2a8cb0e73b086a4306dfbf6d9b3a92
路
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