Instructions to use autoevaluate/extractive-question-answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/extractive-question-answering with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="autoevaluate/extractive-question-answering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("autoevaluate/extractive-question-answering") model = AutoModelForQuestionAnswering.from_pretrained("autoevaluate/extractive-question-answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
d28bc7d | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:2e51cc188180850b8b2fbe3338b6610e3ddf2c4f7b534f6711bffb310ed1ebec
size 3311
|