Instructions to use nlpconnect/dpr-nq-reader-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpconnect/dpr-nq-reader-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nlpconnect/dpr-nq-reader-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nlpconnect/dpr-nq-reader-roberta-base") model = AutoModelForQuestionAnswering.from_pretrained("nlpconnect/dpr-nq-reader-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7879d96d86d24db5701eec8f5965a1a871f29c51b2b306c11e117c26eb8895b
- Size of remote file:
- 496 MB
- SHA256:
- adca871d37492db1cf3c1f03b8a5d84306a329c8ee238356904aa7f70f311771
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.