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 # 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/rubert-tiny-sberquad-6ep-1")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Mathnub/rubert-tiny-sberquad-6ep-1: direct link, hf CLI and curl.
- Browser
- Download file 706 kB
-
https://huggingface.co/Mathnub/rubert-tiny-sberquad-6ep-1/resolve/main/tokenizer.json
- Command line
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hf download hf://Mathnub/rubert-tiny-sberquad-6ep-1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Mathnub/rubert-tiny-sberquad-6ep-1/resolve/main/tokenizer.json
706 kB
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