Instructions to use krinal214/bert-all-squad_que_translated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krinal214/bert-all-squad_que_translated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="krinal214/bert-all-squad_que_translated")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("krinal214/bert-all-squad_que_translated") model = AutoModelForQuestionAnswering.from_pretrained("krinal214/bert-all-squad_que_translated") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8f5bfa314e3bcf782df074f806564f662053f5c38e1d82d3eab4bd32dddc88f
- Size of remote file:
- 3.12 kB
- SHA256:
- 3edf52351dbd85ec85485091cbebf3e96bd17a43429f7fd117616d3690f00f39
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.