Instructions to use deepset/gelectra-base-germanquad-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gelectra-base-germanquad-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/gelectra-base-germanquad-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/gelectra-base-germanquad-distilled") model = AutoModelForQuestionAnswering.from_pretrained("deepset/gelectra-base-germanquad-distilled") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93c71b6481616c624e8687769a5d7b2a9edf3904761c55ad65081b9f017442e7
- Size of remote file:
- 437 MB
- SHA256:
- f5c1a0be8fe054822870fa31ef75c0d0de4015b16ad2516caaa2549caf009b17
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.