Instructions to use deepset/bert-medium-squad2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/bert-medium-squad2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/bert-medium-squad2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/bert-medium-squad2-distilled") model = AutoModelForQuestionAnswering.from_pretrained("deepset/bert-medium-squad2-distilled") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67f8168ba12c6fd7992fdfd35b5d996bd3b1397ebb77065618b87add2eb7fdd3
- Size of remote file:
- 165 MB
- SHA256:
- a9c401109aa56e44e00783606661a8e0fbc14ec96c71f465513d7854ef91564a
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.