Instructions to use deepset/gbert-base-germandpr-question_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gbert-base-germandpr-question_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="deepset/gbert-base-germandpr-question_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepset/gbert-base-germandpr-question_encoder") model = AutoModel.from_pretrained("deepset/gbert-base-germandpr-question_encoder") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9828d6fe1e9002bea7e0f5a5a581b311a9bfa3f98dec517f55c89c887cf5c43
- Size of remote file:
- 440 MB
- SHA256:
- 61025bc67ecb221346fca25f29f66ce7274427d9613aef7aada6cd45488677a7
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