Instructions to use Mathnub/rubert-tiny-sberquad-6ep-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathnub/rubert-tiny-sberquad-6ep-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Mathnub/rubert-tiny-sberquad-6ep-1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Mathnub/rubert-tiny-sberquad-6ep-1") model = AutoModelForQuestionAnswering.from_pretrained("Mathnub/rubert-tiny-sberquad-6ep-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f669fe50cbf3152ab5b8991385409aa7e81ac826808f7714920aa7d1a134e843
- Size of remote file:
- 46.8 MB
- SHA256:
- a3766124e894f6567177aa7b6f04223ffc526faa7108e5ebc81a8ea3b9dcade3
路
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