Instructions to use deepset/gelectra-large-germanquad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gelectra-large-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-large-germanquad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/gelectra-large-germanquad") model = AutoModelForQuestionAnswering.from_pretrained("deepset/gelectra-large-germanquad", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
-
Add evaluation results on the plain_text config of deepset/germanquad
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\ Your model has been evaluated on the plain_text config of the [deepset/germanquad](https://huggingface.co/datasets/deepset/germanquad) dataset by @sjlree, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-deepset__germanquad-7176bd7d-11875590).\ Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=deepset/germanquad).\ Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=deepset/germanquad).dc74381
-
Update README.md
1b7c5a7 -
Update README.md
475addd
-
Update README.md
cfcb7ec
-
Update README.md
c61dedd
-
Update README.md
666a676
-
Update README.md
1def43b -
Update README.md
be7df1f
-
Update README.md
4c80eae
-
Create README.md
e4d8a94
-
init
Ubuntu22d119f -
initial commit
44b8295