Instructions to use deepset/gbert-base-germandpr-reranking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gbert-base-germandpr-reranking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deepset/gbert-base-germandpr-reranking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("deepset/gbert-base-germandpr-reranking") model = AutoModelForSequenceClassification.from_pretrained("deepset/gbert-base-germandpr-reranking") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f29ea052ca7b453fd59844dde833fff2a92fe72640a899441ad44e84f02d48b
- Size of remote file:
- 440 MB
- SHA256:
- 3231778915d3f3242b08b3e8f74f09c607f4989de3a25c9b0fb2531e247568de
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