Instructions to use NchuNLP/Chinese-Question-Answering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NchuNLP/Chinese-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="NchuNLP/Chinese-Question-Answering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("NchuNLP/Chinese-Question-Answering") model = AutoModelForQuestionAnswering.from_pretrained("NchuNLP/Chinese-Question-Answering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NchuNLP/Chinese-Question-Answering: direct link, hf CLI and curl.
- Browser
- Download file 407 MB
-
https://huggingface.co/NchuNLP/Chinese-Question-Answering/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NchuNLP/Chinese-Question-Answering/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NchuNLP/Chinese-Question-Answering/resolve/main/pytorch_model.bin
407 MB
- Xet hash:
- d94173b3f48d187ae61cac27ea8b22a388140c1025ce19cd0f448ff10748e8a0
- Size of remote file:
- 407 MB
- SHA256:
- c4a08ad5e96d1c67cf6aadd7e08bc40ae39cb65146ba8650db067fafca30f19e
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