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
Download pytorch_model.bin from deutsche-telekom/bert-multi-english-german-squad2: direct link, hf CLI and curl.
- Browser
- Download file 709 MB
-
https://huggingface.co/deutsche-telekom/bert-multi-english-german-squad2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deutsche-telekom/bert-multi-english-german-squad2/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/deutsche-telekom/bert-multi-english-german-squad2/resolve/main/pytorch_model.bin
709 MB
- Xet hash:
- 6f4df95643205cf73755333f2cd04a63f4cd831eafb63df3eb3ea4640a4e6c54
- Size of remote file:
- 709 MB
- SHA256:
- 54c6fa599b41d83de95d00a21f25ddecfe836db74d1a17c01e346febc05e7594
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