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 training_args.bin from Mathnub/ruRoberta-sberquad: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/Mathnub/ruRoberta-sberquad/resolve/main/training_args.bin
- Command line
-
hf download hf://Mathnub/ruRoberta-sberquad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mathnub/ruRoberta-sberquad/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- ee1413c7805d617357d1200bfac035eab8f02a0c268bb55bbe726935953b83a1
- Size of remote file:
- 3.58 kB
- SHA256:
- 65e2fab635c76d011aa80c28f2e754628be970db6500e56aee0731396145fbc3
路
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