Instructions to use nlpconnect/roberta-base-squad2-nq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpconnect/roberta-base-squad2-nq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nlpconnect/roberta-base-squad2-nq")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nlpconnect/roberta-base-squad2-nq") model = AutoModelForQuestionAnswering.from_pretrained("nlpconnect/roberta-base-squad2-nq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e963595de9159bd3dd04c3ff5afc0d95ff84a88b3f0c4820e680b065d61a4605
- Size of remote file:
- 1.78 kB
- SHA256:
- 199d948f2bd94d7d2e04dc9a2ec7a7765fd35bc54eab0584cd1b6b5030008047
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.