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
Download training_args.bin from autoevaluate/extractive-question-answering: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/autoevaluate/extractive-question-answering/resolve/main/training_args.bin
- Command line
-
hf download hf://autoevaluate/extractive-question-answering/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/autoevaluate/extractive-question-answering/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- f04510ca1d2cb5ea50ed6a663692abd2d7673a49cbcbcc1b5568e612e00a4275
- Size of remote file:
- 3.31 kB
- SHA256:
- 2e51cc188180850b8b2fbe3338b6610e3ddf2c4f7b534f6711bffb310ed1ebec
路
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