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:
- ded3ff18614bbeb7625f9650afb839b0fb01ac8f7d1c29b980a2985c260dd334
- Size of remote file:
- 3.58 kB
- SHA256:
- aaea6a500f2d4f4979cd8bd8a4275dbf95b46c69e1cc0e7e1ffe845c029a1d63
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.