Instructions to use Mathnub/ruRoberta-sberquad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathnub/ruRoberta-sberquad 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="Mathnub/ruRoberta-sberquad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Mathnub/ruRoberta-sberquad") model = AutoModelForQuestionAnswering.from_pretrained("Mathnub/ruRoberta-sberquad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Mathnub/ruRoberta-sberquad: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/Mathnub/ruRoberta-sberquad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mathnub/ruRoberta-sberquad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mathnub/ruRoberta-sberquad/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 2871c71012e0fdf17863c6e270f59d6fcc1ec90ec4b9cdf779404ad2046340d2
- Size of remote file:
- 1.42 GB
- SHA256:
- ff01dc3cf16ce7b1da3540d963f386a9c0267dfed3d62c8914e556bfea875444
路
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