Instructions to use deepset/gelectra-base-germanquad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gelectra-base-germanquad 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="deepset/gelectra-base-germanquad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/gelectra-base-germanquad") model = AutoModelForQuestionAnswering.from_pretrained("deepset/gelectra-base-germanquad", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/gelectra-base-germanquad: direct link, hf CLI and curl.
- Browser
- Download file 437 MB
-
https://huggingface.co/deepset/gelectra-base-germanquad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepset/gelectra-base-germanquad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/gelectra-base-germanquad/resolve/main/pytorch_model.bin
437 MB
- Xet hash:
- 54c711adcd4c66e156141e2865561f2646628d754086784ee31200a7f67aac8d
- Size of remote file:
- 437 MB
- SHA256:
- 9dcf83684e01e86c54d97c17207a377edfd6aacf4f2ab9133bc5e4f3196cc396
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