Instructions to use microsoft/xdoc-base-squad2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/xdoc-base-squad2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="microsoft/xdoc-base-squad2.0")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("microsoft/xdoc-base-squad2.0") model = AutoModelForQuestionAnswering.from_pretrained("microsoft/xdoc-base-squad2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e352844909f7d248877cd0d3447ee88e86aecf9d6de5a438bb79f63c5af4ba5
- Size of remote file:
- 496 MB
- SHA256:
- 188ede2a871c80413b5e668f5ffc05007d79bf3b7eb78982f74988a55c357ef7
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.