Instructions to use deutsche-telekom/bert-multi-english-german-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deutsche-telekom/bert-multi-english-german-squad2 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="deutsche-telekom/bert-multi-english-german-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deutsche-telekom/bert-multi-english-german-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deutsche-telekom/bert-multi-english-german-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Overview
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- **Language model:** bert-base-multilingual-cased
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- **Language:** German,
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- **Training data:** deQuAD2.0 + SQuAD2.0 training set
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- **Evaluation data:** SQuAD2.0 test set; deQuAD2.0 test set
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- **Infrastructure:** 8xV100 GPU
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## Overview
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- **Language model:** bert-base-multilingual-cased
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- **Language:** German, English
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- **Training data:** deQuAD2.0 + SQuAD2.0 training set
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- **Evaluation data:** SQuAD2.0 test set; deQuAD2.0 test set
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- **Infrastructure:** 8xV100 GPU
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