Instructions to use voidful/question-answering-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/question-answering-zh 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="voidful/question-answering-zh")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("voidful/question-answering-zh") model = AutoModelForQuestionAnswering.from_pretrained("voidful/question-answering-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (837fbeb7af775e545e1ca5e6e34ae7dde586c67a) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>5593f81
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