Instructions to use missvector/ru-asd-qa-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use missvector/ru-asd-qa-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="missvector/ru-asd-qa-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("missvector/ru-asd-qa-bert") model = AutoModelForQuestionAnswering.from_pretrained("missvector/ru-asd-qa-bert") - Notebooks
- Google Colab
- Kaggle
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# results
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on
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It achieves the following results on the evaluation set:
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- Loss: 1.4892
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# results
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the ASD QA dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4892
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